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14 Commits
Author SHA1 Message Date
d0bfb19812 metal: fix memory unwire if model is freed without any GPU operations (#26082)
* metal: fix memory leak if model is freed without any GPU operations

* metal: run dummy work only if residency sets are used

* metal: wrap function in #if defined

* metal: measure system-wide wired memory in test

* metal: always build regression test

Co-authored-by: YiChen Lv <63285796+forforever73@users.noreply.github.com>

---------

Co-authored-by: YiChen Lv <63285796+forforever73@users.noreply.github.com>
2026-07-30 11:11:27 +03:00
Aleksander GrygierandGitHub 21a5f5b7f9 ui: IndexedDB and Conversations data fixes (#26278)
* fix: single-flight conversations store init

* refactor: remove unused legacy-migration util

* fix: make createSystemMessage transactional

* fix: delete message branches cascading on edit/regenerate

* fix: stop stamping lastModified on conversation metadata updates

* fix: count cascaded forks in bulk delete toast, bulkify deleteAll

* refactor: drop redundant conversation list respreads

* refactor: create conversation in a single write

* fix: use table constant in toggleConversationPin

* fix: keep the system message placeholder out of the edit form

* fix: keep focus in the system message editor after opening it

* fix: focus the main chat form after submitting a system message

* fix: update timestamp of the correct conversation on stream completion
2026-07-30 10:10:37 +02:00
Jonathan ClohessyandGitHub 32703b42d6 ggml : Fix issue with kleidiai ci and stringop overflow warning (#26277)
Signed-off-by: Jonathan Clohessy <Jonathan.Clohessy@arm.com>
2026-07-30 09:17:30 +03:00
a6a77bc48d [UT] enhance UT to show all real unsupported backends (#25234)
* enhance UT to show real unsupported backends

* cont : simplify

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2026-07-30 14:04:58 +08:00
64d528be72 mimo2: address MTP review feedback (#26228)
Co-authored-by: tnhnyc <115956684+tnhnyc@users.noreply.github.com>
2026-07-30 11:55:58 +08:00
Aleksander GrygierandGitHub 3018a11e79 fix: increase greeting spacing on md screens (#26287) 2026-07-29 19:25:13 +02:00
Xuan-Son NguyenandGitHub afeebe103b llama: move suppress_tokens handling to common/sampling (#26276)
* llama: move suppress_tokens handling to common/sampling

* address security issues

* rm has_logit_bias
2026-07-29 18:02:30 +02:00
caa596ab3f ggml-cuda : disable MMQ on devices with less than 48 KiB shared memory (#26141)
ggml_cuda_should_use_mmq() selects MMQ purely from the quantization
type. The current MMQ configurations are designed and maintained against
a minimum of 48 KiB per-block shared memory, the limit provided by
NVIDIA Pascal GPUs and later. On devices that report less, no supported
MMQ tile fits and mul_mat_q_switch_J() aborts when every tile size
exceeds the device's per-block shared memory budget.

Disable MMQ when smpbo < 48 KiB so the caller falls back to the BLAS
path instead of hitting GGML_ABORT. Some current MUSA QY1 devices
report only 28 KiB and are covered by this guard.

Reproduced on a Moore Threads MTT S70 (arch mp_21, 28 KiB shared memory
per block) with an RWKV-7 0.1B Q8_0 model:

  $ llama-bench -m rwkv7-g1d-0.1b-Q8_0.gguf -p 128 -n 0
  J_best=0
  ggml/src/ggml-cuda/template-instances/../mmq.cuh:1521: fatal error
  (core dumped)

Only prefill (batch > 1) is affected; token generation is fine. After
the fix the same device falls back to the BLAS path:

  Q8_0    pp128 1470.7 t/s, tg8 55.3 t/s   (was: abort)
  FP16    unchanged
  Q4_K_M  unchanged

This matches a -DGGML_CUDA_FORCE_CUBLAS=ON build (pp128 1464.2 t/s),
which confirms the fallback path is the one being taken.

This is not MUSA-specific: any device with less than 48 KiB per-block
shared memory is affected.

Co-authored-by: KakaruHayate <KakaruHayate@users.noreply.github.com>
2026-07-29 20:27:35 +08:00
TitaniumtownandGitHub 11b068d066 sycl: contiguous fast path + 32-bit index math for unary elementwise ops (#25946)
* sycl: contiguous fast path + 32-bit index math for unary elementwise ops

* sycl: use fastdiv for elementwise index math
2026-07-29 15:16:57 +03:00
Alessandro de Oliveira Faria (A.K.A.CABELO)andGitHub e2f59ed71d vendor: update BoringSSL to 0.20260728.0 (#26241) 2026-07-29 15:16:02 +03:00
Georgi GerganovandGitHub 992c325323 server : add trace logging for slot similarity checking (#26271)
Adds trace logging in server-context.cpp for slot similarity checking
during prompt cache slot selection, including skip reasons and similarity
calculation details.

Assisted-by: llama.cpp:Qwen3.6-27B
2026-07-29 14:59:44 +03:00
Kaben NanlohyandGitHub e1af89a681 conversion: fix Qwen2.5-Omni mmproj conversion regression (#26262) 2026-07-29 12:53:44 +02:00
Aman GuptaandGitHub f5b9bd39b5 RPC: add tensor_memset (#25912) 2026-07-29 15:04:30 +08:00
Geramy LovelessandGitHub 60bccc3763 add rdna3.5, and 3 to mmq configs so they can be tuned independently. (#26199) 2026-07-29 08:43:45 +02:00
35 changed files with 1372 additions and 720 deletions
-4
View File
@@ -294,10 +294,6 @@ struct common_params_sampling {
bool backend_sampling = false;
bool has_logit_bias() const {
return !logit_bias.empty();
}
// print the parameters into a string
std::string print() const;
};
+13 -2
View File
@@ -310,8 +310,19 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, st
}
}
if (params.has_logit_bias()) {
samplers.push_back(llama_sampler_init_logit_bias(llama_vocab_n_tokens(vocab), params.logit_bias.size(), params.logit_bias.data()));
// logit bias: user biases + model suppress tokens (-INFINITY)
{
std::vector<llama_logit_bias> merged = params.logit_bias;
int32_t n_suppress = 0;
const llama_token * suppress = llama_vocab_get_suppress_tokens(vocab, &n_suppress);
for (int32_t i = 0; i < n_suppress; ++i) {
merged.push_back({ suppress[i], -INFINITY });
}
if (!merged.empty()) {
samplers.push_back(llama_sampler_init_logit_bias(llama_vocab_n_tokens(vocab), merged.size(), merged.data()));
}
}
if (params.mirostat == 0) {
+3 -3
View File
@@ -179,12 +179,12 @@ class Qwen25OmniModel(Qwen2VLVisionModel, Qwen25AudioModel):
def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
name, gen = item
if not name.startswith("visual.") and not name.startswith("audio_tower."):
return None
if name.startswith("thinker."):
name = name.replace("thinker.", "")
if not name.startswith("visual.") and not name.startswith("audio_tower."):
return None
if "audio_bos_eos_token" in name:
# this tensor is left unused in transformers code
# https://github.com/huggingface/transformers/blob/6e3063422c4b1c014aa60c32b9254fd2902f0f28/src/transformers/models/qwen2_5_omni/modular_qwen2_5_omni.py#L1809
+2 -2
View File
@@ -6,9 +6,9 @@
extern "C" {
#endif
#define RPC_PROTO_MAJOR_VERSION 4
#define RPC_PROTO_MAJOR_VERSION 5
#define RPC_PROTO_MINOR_VERSION 0
#define RPC_PROTO_PATCH_VERSION 3
#define RPC_PROTO_PATCH_VERSION 0
#ifdef __cplusplus
static_assert(GGML_OP_COUNT == 101, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION");
+1 -1
View File
@@ -2739,7 +2739,7 @@ static block_q8_0x4 make_block_q8_0x4(block_q8_0 * in, unsigned int blck_size_in
return out;
}
static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, unsigned int blck_size_interleave) {
static block_q4_0x4 make_block_q4_0x4(block_q4_0 * in, int blck_size_interleave) {
block_q4_0x4 out;
for (int i = 0; i < 4; i++) {
+278
View File
@@ -0,0 +1,278 @@
static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_rdna3_5(ggml_type type, int J, bool fallback) {
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
}
+278
View File
@@ -0,0 +1,278 @@
static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_rdna3(ggml_type type, int J, bool fallback) {
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
return ggml_cuda_mmq_config(GGML_TYPE_COUNT, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, 256, false, true);
}
+147 -151
View File
@@ -1,77 +1,77 @@
static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config_rdna4(ggml_type type, int J, bool fallback) {
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q1_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_1, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q8_0, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
@@ -79,66 +79,62 @@ static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_conf
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q2_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q2_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q3_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q4_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q5_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_Q6_K, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q6_K, MMQ_ITER_K, false, false);
@@ -146,105 +142,105 @@ static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_conf
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ1_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ2_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q3_K, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_XXS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ3_S, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_XS, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_IQ4_NL, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_0, MMQ_ITER_K, false, false);
@@ -252,27 +248,27 @@ static constexpr __host__ __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_conf
// ---------------------------------------------------------------------------------------------
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_MXFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_Q8_1, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 128, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, true);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 16, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 32, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 48, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 128, 2, 64, 64, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 80, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 96, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
CASE(GGML_TYPE_NVFP4, 256, 2, 128, 112, GGML_CUDA_MMQ_SRAM_LAYOUT_NVFP4, MMQ_ITER_K, false, false);
+9
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@@ -296,6 +296,15 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11, int64_t
return false;
}
// MMQ tiles require at least 48 KiB per-block shared memory; fall back to BLAS otherwise.
{
const int id = ggml_cuda_get_device();
const size_t smpbo = ggml_cuda_info().devices[id].smpbo;
if (smpbo < 48 * 1024) {
return false;
}
}
if (turing_mma_available(cc)) {
return true;
}
+14 -2
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@@ -218,6 +218,8 @@ struct ggml_cuda_mmq_config {
#include "mmq-config-cdna.cuh"
#include "mmq-config-rdna2.cuh"
#include "mmq-config-rdna3.cuh"
#include "mmq-config-rdna3-5.cuh"
#include "mmq-config-rdna4.cuh"
#undef CASE
@@ -227,9 +229,15 @@ static __host__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config(const ggml_type ty
if (GGML_CUDA_CC_IS_CDNA(cc)) {
return ggml_cuda_mmq_get_config_cdna(type, J, fallback);
}
if (amd_wmma_available(cc)) {
if (GGML_CUDA_CC_IS_RDNA4(cc)) {
return ggml_cuda_mmq_get_config_rdna4(type, J, fallback);
}
if (GGML_CUDA_CC_IS_RDNA3_5(cc)) {
return ggml_cuda_mmq_get_config_rdna3_5(type, J, fallback);
}
if (GGML_CUDA_CC_IS_RDNA3(cc)) { // covers RDNA 3.0
return ggml_cuda_mmq_get_config_rdna3(type, J, fallback);
}
return ggml_cuda_mmq_get_config_rdna2(type, J, fallback);
}
if (blackwell_mma_available(cc)) {
@@ -245,8 +253,12 @@ static constexpr __device__ ggml_cuda_mmq_config ggml_cuda_mmq_get_config(ggml_t
#ifdef GGML_USE_HIP
#ifdef CDNA
return ggml_cuda_mmq_get_config_cdna(type, J, fallback);
#elif defined(AMD_WMMA_AVAILABLE)
#elif defined(RDNA4)
return ggml_cuda_mmq_get_config_rdna4(type, J, fallback);
#elif defined(RDNA3_5)
return ggml_cuda_mmq_get_config_rdna3_5(type, J, fallback);
#elif defined(RDNA3)
return ggml_cuda_mmq_get_config_rdna3(type, J, fallback);
#else
return ggml_cuda_mmq_get_config_rdna2(type, J, fallback);
#endif // CDNA
+1 -1
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@@ -213,7 +213,7 @@ typedef void * ggml_metal_rset_t;
// a collection of residency sets (non-owning)
typedef struct ggml_metal_rsets * ggml_metal_rsets_t;
ggml_metal_rsets_t ggml_metal_rsets_init(void);
ggml_metal_rsets_t ggml_metal_rsets_init(ggml_metal_device_t dev);
void ggml_metal_rsets_free(ggml_metal_rsets_t rsets);
//
+37 -2
View File
@@ -557,7 +557,32 @@ struct ggml_metal_rsets {
dispatch_group_t d_group;
};
ggml_metal_rsets_t ggml_metal_rsets_init(void) {
#if defined(GGML_METAL_HAS_RESIDENCY_SETS)
static void ggml_metal_dummy_work(ggml_metal_device_t dev) {
if (dev->mtl_queue == nil) {
return;
}
@autoreleasepool {
// perform a minimal dummy operation on the GPU
id<MTLBuffer> buf = [dev->mtl_device newBufferWithLength:1 options:MTLResourceStorageModePrivate];
id<MTLCommandBuffer> cmd_buf = [dev->mtl_queue commandBuffer];
{
id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
[encoder fillBuffer:buf range:NSMakeRange(0, 1) value:0];
[encoder endEncoding];
}
[cmd_buf commit];
[buf release];
}
}
#endif
ggml_metal_rsets_t ggml_metal_rsets_init(ggml_metal_device_t dev) {
ggml_metal_rsets_t res = calloc(1, sizeof(struct ggml_metal_rsets));
res->lock = [[NSLock alloc] init];
@@ -610,6 +635,15 @@ ggml_metal_rsets_t ggml_metal_rsets_init(void) {
#endif
});
#if defined(GGML_METAL_HAS_RESIDENCY_SETS)
if (@available(macOS 15.0, iOS 18.0, tvOS 18.0, visionOS 2.0, *)) {
// workaround for residency set memory not being released if no GPU operation occurs
// https://developer.apple.com/forums/thread/839089
// https://github.com/ggml-org/llama.cpp/issues/25937
ggml_metal_dummy_work(dev);
}
#endif
return res;
}
@@ -864,7 +898,7 @@ ggml_metal_device_t ggml_metal_device_init(int device) {
}
if (dev->props.use_residency_sets) {
dev->rsets = ggml_metal_rsets_init();
dev->rsets = ggml_metal_rsets_init(dev);
} else {
dev->rsets = nil;
}
@@ -1484,6 +1518,7 @@ static void ggml_metal_buffer_rset_free(ggml_metal_buffer_t buf) {
if (buf->rset) {
[buf->rset endResidency];
[buf->rset removeAllAllocations];
[buf->rset commit];
[buf->rset release];
}
}
+82 -1
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@@ -71,6 +71,7 @@ enum rpc_cmd {
RPC_CMD_HELLO,
RPC_CMD_DEVICE_COUNT,
RPC_CMD_GRAPH_RECOMPUTE,
RPC_CMD_MEMSET_TENSOR,
RPC_CMD_COUNT,
};
@@ -152,6 +153,13 @@ struct rpc_msg_buffer_clear_req {
uint8_t value;
};
struct rpc_msg_memset_tensor_req {
rpc_tensor tensor;
uint64_t offset;
uint64_t size;
uint8_t value;
};
struct rpc_msg_set_tensor_hash_req {
rpc_tensor tensor;
uint64_t offset;
@@ -462,6 +470,19 @@ static enum ggml_status ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_
return GGML_STATUS_SUCCESS;
}
static void ggml_backend_rpc_buffer_memset_tensor(
ggml_backend_buffer_t buffer, ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
rpc_msg_memset_tensor_req request = {
/* .tensor = */ serialize_tensor(tensor),
/* .offset = */ offset,
/* .size = */ size,
/* .value = */ value,
};
bool status = send_rpc_cmd(ctx->sock, RPC_CMD_MEMSET_TENSOR, &request, sizeof(request), nullptr, 0);
RPC_STATUS_ASSERT(status);
}
static void ggml_backend_rpc_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
rpc_tensor rpc_tensor = serialize_tensor(tensor);
@@ -531,7 +552,7 @@ static ggml_backend_buffer_i ggml_backend_rpc_buffer_interface = {
/* .free_buffer = */ ggml_backend_rpc_buffer_free_buffer,
/* .get_base = */ ggml_backend_rpc_buffer_get_base,
/* .init_tensor = */ ggml_backend_rpc_buffer_init_tensor,
/* .memset_tensor = */ NULL,
/* .memset_tensor = */ ggml_backend_rpc_buffer_memset_tensor,
/* .set_tensor = */ ggml_backend_rpc_buffer_set_tensor,
/* .get_tensor = */ ggml_backend_rpc_buffer_get_tensor,
/* .set_tensor_2d = */ NULL,
@@ -831,6 +852,7 @@ public:
bool buffer_get_base(const rpc_msg_buffer_get_base_req & request, rpc_msg_buffer_get_base_rsp & response);
bool free_buffer(const rpc_msg_free_buffer_req & request);
bool buffer_clear(const rpc_msg_buffer_clear_req & request);
bool memset_tensor(const rpc_msg_memset_tensor_req & request);
bool set_tensor(const std::vector<uint8_t> & input);
bool set_tensor_hash(const rpc_msg_set_tensor_hash_req & request, rpc_msg_set_tensor_hash_rsp & response);
bool get_tensor(const rpc_msg_get_tensor_req & request, std::vector<uint8_t> & response);
@@ -989,6 +1011,52 @@ bool rpc_server::buffer_clear(const rpc_msg_buffer_clear_req & request) {
return true;
}
bool rpc_server::memset_tensor(const rpc_msg_memset_tensor_req & request) {
struct ggml_init_params params {
/*.mem_size =*/ ggml_tensor_overhead(),
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr || tensor->buffer == nullptr) {
GGML_LOG_ERROR("[%s] error deserializing tensor\n", __func__);
return false;
}
const uint64_t tensor_size = ggml_nbytes(tensor);
if (request.offset > tensor_size || request.size > tensor_size - request.offset) {
GGML_LOG_ERROR("[%s] tensor region (offset=%" PRIu64 ", size=%" PRIu64 ") out of tensor bounds [0, %" PRIu64 ")\n",
__func__, request.offset, request.size, tensor_size);
return false;
}
const uint64_t buffer_start = (uint64_t) ggml_backend_buffer_get_base(tensor->buffer);
const uint64_t buffer_size = ggml_backend_buffer_get_size(tensor->buffer);
if (request.tensor.data < buffer_start) {
GGML_LOG_ERROR("[%s] tensor data before buffer start\n", __func__);
return false;
}
const uint64_t data_offset = request.tensor.data - buffer_start;
if (data_offset > buffer_size ||
request.offset > buffer_size - data_offset ||
request.size > buffer_size - data_offset - request.offset) {
GGML_LOG_ERROR("[%s] tensor region out of buffer bounds\n", __func__);
return false;
}
if (tensor->buffer->iface.memset_tensor == nullptr) {
GGML_LOG_ERROR("[%s] memset not implemented by backend buffer\n", __func__);
return false;
}
LOG_DBG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %" PRIu64 ", value: %u\n",
__func__, (void *) tensor->buffer, tensor->data, request.offset, request.size, request.value);
ggml_backend_tensor_memset(tensor, request.value, request.offset, request.size);
return true;
}
ggml_tensor * rpc_server::deserialize_tensor(struct ggml_context * ctx, const rpc_tensor * tensor) {
// Validate tensor type before using it
if (tensor->type >= GGML_TYPE_COUNT) {
@@ -1585,6 +1653,19 @@ static void rpc_serve_client(const std::vector<ggml_backend_t> & backends, const
}
break;
}
case RPC_CMD_MEMSET_TENSOR: {
rpc_msg_memset_tensor_req request;
if (!recv_msg(sock, &request, sizeof(request))) {
return;
}
if (!server.memset_tensor(request)) {
return;
}
if (!send_msg(sock, nullptr, 0)) {
return;
}
break;
}
case RPC_CMD_SET_TENSOR: {
std::vector<uint8_t> input;
if (!recv_msg(sock, input)) {
+87 -42
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@@ -306,29 +306,43 @@ static __dpct_inline__ T op_trunc(T x) {
}
}
template<typename T, typename F>
static void unary_op_flat_kernel(const T * x, T * dst, const int k, const sycl::nd_item<1> & item_ct1, F func) {
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
dst[i] = func(x[i]);
}
}
template<typename T, typename F>
static void unary_op_generic_kernel(
const T * x,
T * dst,
const int k,
const int64_t ne0, const int64_t ne1, const int64_t ne2, const int64_t ne3,
const sycl::uint3 ne0_fd, const sycl::uint3 ne1_fd, const sycl::uint3 ne2_fd,
const size_t nb0, const size_t nb1, const size_t nb2, const size_t nb3,
const size_t nbd0, const size_t nbd1, const size_t nbd2, const size_t nbd3,
const sycl::nd_item<1> & item_ct1,
F func) {
(void) ne3;
// 32-bit index math: k is int, so every logical index fits u32. 64-bit integer div/mod is
// emulated on Xe and dominates this kernel otherwise, and even the 32-bit divide is worth
// avoiding -- the divisors are launch-invariant, so the magic numbers are precomputed
// host-side and each division becomes a multiply-high plus a shift.
// Byte offsets are widened back to size_t only for the final address math.
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
const int64_t i0 = i % ne0;
const int64_t i1 = (i / ne0) % ne1;
const int64_t i2 = (i / (ne0*ne1)) % ne2;
const int64_t i3 = i / (ne0*ne1*ne2);
sycl::uint2 dm = fast_div_modulo((uint32_t) i, ne0_fd);
const uint32_t i0 = dm.y();
dm = fast_div_modulo(dm.x(), ne1_fd);
const uint32_t i1 = dm.y();
dm = fast_div_modulo(dm.x(), ne2_fd);
const uint32_t i2 = dm.y();
const uint32_t i3 = dm.x();
const char * src_base = (const char *) x;
char * dst_base = (char *) dst;
const T * srcp = (const T *)(src_base + i0*nb0 + i1*nb1 + i2*nb2 + i3*nb3 );
T * dstp = (T *)(dst_base + i0*nbd0 + i1*nbd1 + i2*nbd2 + i3*nbd3);
const T * srcp = (const T *)(src_base + (size_t) i0*nb0 + (size_t) i1*nb1 + (size_t) i2*nb2 + (size_t) i3*nb3 );
T * dstp = (T *)(dst_base + (size_t) i0*nbd0 + (size_t) i1*nbd1 + (size_t) i2*nbd2 + (size_t) i3*nbd3);
*dstp = func(*srcp);
}
@@ -407,46 +421,51 @@ static void clamp(const T * x, T * dst, const float min, const float max, const
}
template<typename T>
static void gated_op_fused_geglu(const T * x, const T * g, T * dst, const uint64_t k, const uint64_t n, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
static void gated_op_fused_geglu(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
const int64_t j0 = (i / n) * o0 + (i % n);
const int64_t j1 = o0 == o1 ? j0 : (i / n) * o1 + (i % n);
const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd);
const int64_t j0 = rc.x() * o0 + rc.y();
const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y();
dst[i] = op_gelu(x[j0]) * g[j1];
}
}
template<typename T>
static void gated_op_fused_reglu(const T * x, const T * g, T * dst, const uint64_t k, const uint64_t n, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
static void gated_op_fused_reglu(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
const int64_t j0 = (i / n) * o0 + (i % n);
const int64_t j1 = o0 == o1 ? j0 : (i / n) * o1 + (i % n);
const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd);
const int64_t j0 = rc.x() * o0 + rc.y();
const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y();
dst[i] = op_relu(x[j0]) * g[j1];
}
}
template<typename T>
static void gated_op_fused_swiglu(const T * x, const T * g, T * dst, const uint64_t k, const uint64_t n, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
static void gated_op_fused_swiglu(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
const int64_t j0 = (i / n) * o0 + (i % n);
const int64_t j1 = o0 == o1 ? j0 : (i / n) * o1 + (i % n);
const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd);
const int64_t j0 = rc.x() * o0 + rc.y();
const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y();
dst[i] = op_silu(x[j0]) * g[j1];
}
}
template<typename T>
static void gated_op_fused_geglu_erf(const T * x, const T * g, T * dst, const uint64_t k, const uint64_t n, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
static void gated_op_fused_geglu_erf(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
const int64_t j0 = (i / n) * o0 + (i % n);
const int64_t j1 = o0 == o1 ? j0 : (i / n) * o1 + (i % n);
const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd);
const int64_t j0 = rc.x() * o0 + rc.y();
const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y();
dst[i] = op_gelu_erf(x[j0]) * g[j1];
}
}
template<typename T>
static void gated_op_fused_geglu_quick(const T * x, const T * g, T * dst, const uint64_t k, const uint64_t n, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
static void gated_op_fused_geglu_quick(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) {
SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
const int64_t j0 = (i / n) * o0 + (i % n);
const int64_t j1 = o0 == o1 ? j0 : (i / n) * o1 + (i % n);
const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd);
const int64_t j0 = rc.x() * o0 + rc.y();
const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y();
dst[i] = op_gelu_quick(x[j0]) * g[j1];
}
}
@@ -529,6 +548,10 @@ static inline void dispatch_ggml_sycl_op_fused_glu(ggml_backend_sycl_context & c
GGML_ASSERT(dst->ne[0] == nc);
GGML_ASSERT(ggml_is_contiguous_1(dst->src[0]));
GGML_ASSERT(ggml_is_contiguous(dst));
// The fused GLU kernels index with 32-bit fastdiv, which is exact only for indices below
// 2^31. A dst that large is ~8 GB at f32, and the grid sizing already narrows to 32 bits,
// so assert the bound rather than carry a second code path for it.
GGML_ASSERT(ggml_nelements(dst) < ((int64_t) 1 << 31));
const int32_t swapped = ((const int32_t *) dst->op_params)[1];
void * src0_d = src0->data;
void * src1_d = src1 ? src1->data : src0->data;
@@ -597,7 +620,6 @@ static inline void ggml_sycl_op_unary(
const int64_t ne0 = dst->ne[0];
const int64_t ne1 = dst->ne[1];
const int64_t ne2 = dst->ne[2];
const int64_t ne3 = dst->ne[3];
const size_t nb0 = src0->nb[0];
const size_t nb1 = src0->nb[1];
@@ -609,24 +631,42 @@ static inline void ggml_sycl_op_unary(
const size_t nbd2 = dst->nb[2];
const size_t nbd3 = dst->nb[3];
// Hot unary ops (FFN/GDN silu, sigmoid, ...) run on contiguous tensors;
// skip the strided index math entirely for them.
const bool contiguous = ggml_is_contiguous(src0) && ggml_is_contiguous(dst);
ggml_sycl_detail::dispatch_ggml_sycl_op_unary(ctx, dst,
[=](const auto* src, auto* dst_ptr, int k_elements, queue_ptr stream) {
const int num_blocks = ceil_div(k_elements, 256);
stream->parallel_for(
sycl::nd_range<1>(sycl::range<1>(num_blocks) * sycl::range<1>(256),
sycl::range<1>(256)),
[=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
unary_op_generic_kernel(
src, dst_ptr, k_elements,
ne0, ne1, ne2, ne3,
nb0, nb1, nb2, nb3,
nbd0, nbd1, nbd2, nbd3,
item_ct1,
func
);
});
if (contiguous) {
stream->parallel_for(
sycl::nd_range<1>(sycl::range<1>(num_blocks) * sycl::range<1>(256),
sycl::range<1>(256)),
[=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
unary_op_flat_kernel(src, dst_ptr, k_elements, item_ct1, func);
});
} else {
// Launch-invariant divisors: compute the magic numbers once on the host so the
// kernel never issues an integer divide. Only the strided path needs them.
const sycl::uint3 ne0_fd = init_fastdiv_values((uint32_t) ne0);
const sycl::uint3 ne1_fd = init_fastdiv_values((uint32_t) ne1);
const sycl::uint3 ne2_fd = init_fastdiv_values((uint32_t) ne2);
stream->parallel_for(
sycl::nd_range<1>(sycl::range<1>(num_blocks) * sycl::range<1>(256),
sycl::range<1>(256)),
[=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
unary_op_generic_kernel(
src, dst_ptr, k_elements,
ne0_fd, ne1_fd, ne2_fd,
nb0, nb1, nb2, nb3,
nbd0, nbd1, nbd2, nbd3,
item_ct1,
func
);
});
}
});
}
@@ -930,10 +970,11 @@ static inline void ggml_sycl_op_geglu(ggml_backend_sycl_context & ctx, ggml_tens
ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst,
[](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) {
const uint32_t num_blocks = ceil_div(k, SYCL_GELU_BLOCK_SIZE);
const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n);
main_stream->parallel_for(
sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_GELU_BLOCK_SIZE)),
sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
gated_op_fused_geglu(x_ptr, g_ptr, dst_ptr, k, n, o0, o1, item_ct1);
gated_op_fused_geglu(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1);
});
});
}
@@ -942,10 +983,11 @@ static inline void ggml_sycl_op_reglu(ggml_backend_sycl_context & ctx, ggml_tens
ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst,
[](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) {
const uint32_t num_blocks = ceil_div((uint32_t)k, SYCL_RELU_BLOCK_SIZE); // Using RELU block size for reglu
const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n);
main_stream->parallel_for(
sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_RELU_BLOCK_SIZE)),
sycl::range<1>(SYCL_RELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
gated_op_fused_reglu(x_ptr, g_ptr, dst_ptr, k, n, o0, o1, item_ct1);
gated_op_fused_reglu(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1);
});
});
}
@@ -954,10 +996,11 @@ static inline void ggml_sycl_op_swiglu(ggml_backend_sycl_context & ctx, ggml_ten
ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst,
[](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) {
const uint32_t num_blocks = ceil_div((uint32_t)k, SYCL_SILU_BLOCK_SIZE); // Using SILU block size for swiglu
const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n);
main_stream->parallel_for(
sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_SILU_BLOCK_SIZE)),
sycl::range<1>(SYCL_SILU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
gated_op_fused_swiglu(x_ptr, g_ptr, dst_ptr, k, n, o0, o1, item_ct1);
gated_op_fused_swiglu(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1);
});
});
}
@@ -1057,10 +1100,11 @@ static inline void ggml_sycl_op_geglu_erf(ggml_backend_sycl_context & ctx, ggml_
ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst,
[](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) {
const uint32_t num_blocks = ceil_div(k, SYCL_GELU_BLOCK_SIZE);
const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n);
main_stream->parallel_for(
sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_GELU_BLOCK_SIZE)),
sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
gated_op_fused_geglu_erf(x_ptr, g_ptr, dst_ptr, k, n, o0, o1, item_ct1);
gated_op_fused_geglu_erf(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1);
});
});
}
@@ -1069,10 +1113,11 @@ static inline void ggml_sycl_op_geglu_quick(ggml_backend_sycl_context & ctx, ggm
ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst,
[](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) {
const uint32_t num_blocks = ceil_div(k, SYCL_GELU_BLOCK_SIZE);
const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n);
main_stream->parallel_for(
sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_GELU_BLOCK_SIZE)),
sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
gated_op_fused_geglu_quick(x_ptr, g_ptr, dst_ptr, k, n, o0, o1, item_ct1);
gated_op_fused_geglu_quick(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1);
});
});
}
+3
View File
@@ -4440,8 +4440,11 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.FFN_EXP_PROBS_B,
MODEL_TENSOR.LAYER_OUT_NORM,
MODEL_TENSOR.NEXTN_EH_PROJ,
MODEL_TENSOR.NEXTN_EMBED_TOKENS,
MODEL_TENSOR.NEXTN_ENORM,
MODEL_TENSOR.NEXTN_HNORM,
MODEL_TENSOR.NEXTN_SHARED_HEAD_HEAD,
MODEL_TENSOR.NEXTN_SHARED_HEAD_NORM,
],
MODEL_ARCH.STEP35: [
MODEL_TENSOR.TOKEN_EMBD,
+3
View File
@@ -1102,6 +1102,9 @@ extern "C" {
LLAMA_API bool llama_vocab_get_add_eos(const struct llama_vocab * vocab);
LLAMA_API bool llama_vocab_get_add_sep(const struct llama_vocab * vocab);
// model-specific suppress tokens (gguf key: tokenizer.ggml.suppress_tokens)
LLAMA_API const llama_token * llama_vocab_get_suppress_tokens(const struct llama_vocab * vocab, int32_t * n_suppress_tokens);
LLAMA_API llama_token llama_vocab_fim_pre(const struct llama_vocab * vocab);
LLAMA_API llama_token llama_vocab_fim_suf(const struct llama_vocab * vocab);
LLAMA_API llama_token llama_vocab_fim_mid(const struct llama_vocab * vocab);
+3 -1
View File
@@ -2243,7 +2243,9 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
filter = [&](uint32_t il) { return il >= hparams.n_layer(); };
}
if ((arch == LLM_ARCH_STEP35 || arch == LLM_ARCH_HY_V3 || arch == LLM_ARCH_GLM_DSA) && hparams.n_layer_nextn > 0) {
if ((arch == LLM_ARCH_STEP35 || arch == LLM_ARCH_HY_V3 || arch == LLM_ARCH_GLM_DSA ||
arch == LLM_ARCH_MIMO2) &&
hparams.n_layer_nextn > 0) {
if (params.ctx_type == LLAMA_CONTEXT_TYPE_MTP) {
filter = [&](uint32_t il) { return il >= hparams.n_layer(); };
} else {
+16 -1
View File
@@ -2578,7 +2578,14 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
if (suppress_idx != -1) {
const int n = gguf_get_arr_n(ctx, suppress_idx);
const int32_t * data = (const int32_t *) gguf_get_arr_data(ctx, suppress_idx);
suppress_tokens.assign(data, data + n);
// drop out-of-range ids
suppress_tokens.reserve(n);
for (int i = 0; i < n; ++i) {
const int32_t id = data[i];
if (id >= 0 && id < (int) id_to_token.size()) {
suppress_tokens.push_back(id);
}
}
}
}
@@ -4205,6 +4212,14 @@ bool llama_vocab_get_add_sep(const struct llama_vocab * vocab) {
return vocab->get_add_sep();
}
const llama_token * llama_vocab_get_suppress_tokens(const struct llama_vocab * vocab, int32_t * n_suppress_tokens) {
const std::vector<llama_token> & tokens = vocab->get_suppress_tokens();
if (n_suppress_tokens) {
*n_suppress_tokens = (int32_t) tokens.size();
}
return tokens.data();
}
llama_token llama_vocab_fim_pre(const struct llama_vocab * vocab) {
return vocab->token_fim_pre();
}
-37
View File
@@ -142,33 +142,6 @@ static ggml_tensor * ggml_view_2d_slice(ggml_context * ctx0, ggml_tensor * x, in
idx * x->ne[0] * x->ne[1] * ggml_element_size(x));
}
// TODO @ngxson : maybe improve this in the future
class llm_graph_input_logits_bias : public llm_graph_input_i {
public:
llm_graph_input_logits_bias(const llama_vocab & vocab) {
arr.resize(vocab.n_tokens(), 0.0f);
for (llama_token id : vocab.get_suppress_tokens()) {
if (0 <= id && id < (int32_t)vocab.n_tokens()) {
arr[id] = -INFINITY;
}
}
}
virtual ~llm_graph_input_logits_bias() = default;
void set_input(const llama_ubatch * /*ubatch*/) override {
const int64_t n_vocab = arr.size();
ggml_backend_tensor_set(logits_bias, arr.data(), 0, n_vocab*ggml_element_size(logits_bias));
}
bool can_reuse(const llm_graph_params & /*params*/) override {
return true;
}
ggml_tensor * logits_bias = nullptr; // F32 [n_vocab]
std::vector<float> arr;
};
llama_model_gemma4::graph::graph(const llama_model & model, const llm_graph_params & params) :
llm_graph_context(params),
model(model),
@@ -429,16 +402,6 @@ llama_model_gemma4::graph::graph(const llama_model & model, const llm_graph_para
cur = ggml_scale(ctx0, cur, hparams.f_final_logit_softcapping);
}
// apply logits bias if needed (e.g. for gemma4_unified patch)
// this is to mirror the suppress_tokens patch on transformers, to avoid model from outputing <image|> and <audio|> tokens (which is a known issue related to the checkpoint)
// TODO: maybe handle this inside the sampling system in the future
if (!model.vocab.get_suppress_tokens().empty()) {
auto inp_bias = std::make_unique<llm_graph_input_logits_bias>(model.vocab);
inp_bias->logits_bias = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, inp_bias->arr.size());
cur = ggml_add(ctx0, cur, inp_bias->logits_bias);
res->add_input(std::move(inp_bias));
}
cb(cur, "result_output", -1);
res->t_logits = cur;
+181 -21
View File
@@ -25,9 +25,13 @@ void llama_model_mimo2::load_arch_hparams(llama_model_loader & ml) {
}
}
void llama_model_mimo2::load_arch_tensors(llama_model_loader &) {
void llama_model_mimo2::load_arch_tensors(llama_model_loader & ml) {
LLAMA_LOAD_LOCALS;
const std::string mtp_probe = "blk." + std::to_string(n_layer) + ".nextn.eh_proj.weight";
const bool trunk_only = (hparams.n_layer_nextn > 0) && (ml.get_weight(mtp_probe.c_str()) == nullptr);
const int mtp_flags = trunk_only ? TENSOR_NOT_REQUIRED : 0;
tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
// output
@@ -40,41 +44,46 @@ void llama_model_mimo2::load_arch_tensors(llama_model_loader &) {
uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa(i);
uint32_t n_head = hparams.n_head(i);
// NextN/MTP layers (the last n_nextn blocks) are preserved but disabled pending support
const bool is_nextn = i >= n_layer;
const int skip = is_nextn ? TENSOR_SKIP : 0;
const int flags = is_nextn ? mtp_flags : 0;
create_tensor_qkv(layer, i, n_embd, n_embd_head_k * n_head, n_embd_k_gqa, n_embd_v_gqa, skip);
layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), { n_embd_head_v * n_head, n_embd }, skip);
create_tensor_qkv(layer, i, n_embd, n_embd_head_k * n_head, n_embd_k_gqa, n_embd_v_gqa, flags);
layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), { n_embd_head_v * n_head, n_embd }, flags);
layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, skip);
layer.attn_sinks = create_tensor(tn(LLM_TENSOR_ATTN_SINKS, "weight", i), {n_head}, TENSOR_NOT_REQUIRED | skip);
layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, flags);
layer.attn_sinks = create_tensor(tn(LLM_TENSOR_ATTN_SINKS, "weight", i), {n_head}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, skip);
layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, flags);
// non-MoE branch
layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED | flags);
// MoE branch
int64_t n_ff_exp = hparams.n_ff_exp;
layer.ffn_gate_inp = create_tensor(tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_gate_exps = create_tensor(tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd, n_ff_exp, n_expert}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_down_exps = create_tensor(tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp, n_embd, n_expert}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_up_exps = create_tensor(tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), {n_embd, n_ff_exp, n_expert}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_exp_probs_b = create_tensor(tn(LLM_TENSOR_FFN_EXP_PROBS_B, "bias", i), {n_expert}, TENSOR_NOT_REQUIRED | skip);
layer.ffn_gate_inp = create_tensor(tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_gate_exps = create_tensor(tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd, n_ff_exp, n_expert}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_down_exps = create_tensor(tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp, n_embd, n_expert}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_up_exps = create_tensor(tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), {n_embd, n_ff_exp, n_expert}, TENSOR_NOT_REQUIRED | flags);
layer.ffn_exp_probs_b = create_tensor(tn(LLM_TENSOR_FFN_EXP_PROBS_B, "bias", i), {n_expert}, TENSOR_NOT_REQUIRED | flags);
if (is_nextn) {
layer.nextn.eh_proj = create_tensor(tn(LLM_TENSOR_NEXTN_EH_PROJ, "weight", i), {2 * n_embd, n_embd}, skip);
layer.nextn.enorm = create_tensor(tn(LLM_TENSOR_NEXTN_ENORM, "weight", i), {n_embd}, skip);
layer.nextn.hnorm = create_tensor(tn(LLM_TENSOR_NEXTN_HNORM, "weight", i), {n_embd}, skip);
layer.layer_out_norm = create_tensor(tn(LLM_TENSOR_LAYER_OUT_NORM, "weight", i), {n_embd}, skip);
layer.nextn.eh_proj = create_tensor(tn(LLM_TENSOR_NEXTN_EH_PROJ, "weight", i), {2 * n_embd, n_embd}, flags);
layer.nextn.enorm = create_tensor(tn(LLM_TENSOR_NEXTN_ENORM, "weight", i), {n_embd}, flags);
layer.nextn.hnorm = create_tensor(tn(LLM_TENSOR_NEXTN_HNORM, "weight", i), {n_embd}, flags);
layer.nextn.embed_tokens = create_tensor(tn(LLM_TENSOR_NEXTN_EMBED_TOKENS, "weight", i), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED | flags);
layer.nextn.shared_head_head = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD, "weight", i), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED | flags);
layer.nextn.shared_head_norm = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, "weight", i), {n_embd}, TENSOR_NOT_REQUIRED | flags);
layer.layer_out_norm = create_tensor(tn(LLM_TENSOR_LAYER_OUT_NORM, "weight", i), {n_embd}, TENSOR_NOT_REQUIRED | flags);
}
}
}
std::unique_ptr<llm_graph_context> llama_model_mimo2::build_arch_graph(const llm_graph_params & params) const {
if (params.gtype == LLM_GRAPH_TYPE_DECODER_MTP) {
return std::make_unique<graph_mtp>(*this, params);
}
return std::make_unique<graph>(*this, params);
}
@@ -89,6 +98,8 @@ llama_model_mimo2::graph::graph(const llama_model & model, const llm_graph_param
ggml_tensor * inp_out_ids = build_inp_out_ids();
const float v_scale = hparams.f_attn_value_scale;
const bool emit_h_nextn = cparams.embeddings_nextn;
const bool crop_last_layer = inp_out_ids && (!emit_h_nextn || cparams.embeddings_nextn_masked);
for (int il = 0; il < n_layer; ++il) {
ggml_tensor * inpSA = inpL;
@@ -168,7 +179,7 @@ llama_model_mimo2::graph::graph(const llama_model & model, const llm_graph_param
}
}
if (il == n_layer - 1 && inp_out_ids) {
if (il == n_layer - 1 && crop_last_layer) {
cur = ggml_get_rows(ctx0, cur, inp_out_ids);
inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
}
@@ -218,6 +229,15 @@ llama_model_mimo2::graph::graph(const llama_model & model, const llm_graph_param
cur = inpL;
if (emit_h_nextn) {
cb(cur, "h_nextn", -1);
res->t_h_nextn = cur;
if (!cparams.embeddings_nextn_masked && inp_out_ids) {
cur = ggml_get_rows(ctx0, cur, inp_out_ids);
}
}
cur = build_norm(cur,
model.output_norm, NULL,
LLM_NORM_RMS, -1);
@@ -233,3 +253,143 @@ llama_model_mimo2::graph::graph(const llama_model & model, const llm_graph_param
ggml_build_forward_expand(gf, cur);
}
// Mirrors MiMo's appended NextN block: normalize and fuse token and hidden inputs, run the decoder block,
// expose its pre-head-norm state to the next draft step, then apply the shared output norm and LM head.
// Converted checkpoints may store that shared norm as layer_out_norm, so it remains in the fallback chain.
llama_model_mimo2::graph_mtp::graph_mtp(const llama_model & model, const llm_graph_params & params)
: llm_graph_context(params) {
GGML_ASSERT(hparams.n_layer_nextn > 0 && "MIMO2 MTP requires n_layer_nextn > 0");
const int il = hparams.n_layer() + cparams.nextn_layer_offset;
GGML_ASSERT(cparams.nextn_layer_offset >= 0 &&
cparams.nextn_layer_offset < (int) hparams.n_layer_nextn &&
"nextn_layer_offset out of range [0, n_layer_nextn)");
const auto & layer = model.layers[il];
GGML_ASSERT(layer.nextn.eh_proj && "MIMO2 MTP block missing nextn.eh_proj");
GGML_ASSERT(layer.nextn.enorm && "MIMO2 MTP block missing nextn.enorm");
GGML_ASSERT(layer.nextn.hnorm && "MIMO2 MTP block missing nextn.hnorm");
GGML_ASSERT(layer.wqkv && "MIMO2 MTP requires fused attn_qkv");
const uint32_t n_head_l = hparams.n_head(il);
const uint32_t n_head_kv_l = hparams.n_head_kv(il);
const float freq_base_l = model.get_rope_freq_base(cparams, il);
const float freq_scale_l = model.get_rope_freq_scale(cparams, il);
const float v_scale = hparams.f_attn_value_scale;
auto inp = std::make_unique<llm_graph_input_embd>(hparams.n_embd);
inp->tokens = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_tokens);
ggml_set_input(inp->tokens);
inp->embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, hparams.n_embd, n_tokens);
ggml_set_input(inp->embd);
ggml_set_name(inp->embd, "mtp_h_input");
ggml_tensor * tok_embd_w = layer.nextn.embed_tokens ? layer.nextn.embed_tokens : model.tok_embd;
ggml_tensor * h_input = inp->embd;
ggml_tensor * tok_embd = ggml_get_rows(ctx0, tok_embd_w, inp->tokens);
cb(tok_embd, "mtp_tok_embd", il);
res->add_input(std::move(inp));
ggml_tensor * inp_pos = build_inp_pos();
ggml_tensor * inp_out_ids = build_inp_out_ids();
auto * inp_attn = build_attn_inp_kv_iswa();
ggml_tensor * h_norm = build_norm(h_input, layer.nextn.hnorm, nullptr, LLM_NORM_RMS, il);
cb(h_norm, "mtp_hnorm", il);
ggml_tensor * e_norm = build_norm(tok_embd, layer.nextn.enorm, nullptr, LLM_NORM_RMS, il);
cb(e_norm, "mtp_enorm", il);
ggml_tensor * concat = ggml_concat(ctx0, e_norm, h_norm, /*dim=*/ 0);
cb(concat, "mtp_concat", il);
ggml_tensor * cur = build_lora_mm(layer.nextn.eh_proj, concat, layer.nextn.eh_proj_s);
cb(cur, "mtp_eh_proj", il);
ggml_tensor * inpSA = cur;
cur = build_norm(cur, layer.attn_norm, nullptr, LLM_NORM_RMS, il);
cb(cur, "mtp_attn_norm", il);
ggml_tensor * qkv = build_lora_mm(layer.wqkv, cur, layer.wqkv_s);
cb(qkv, "mtp_wqkv", il);
const size_t row_k = ggml_row_size(qkv->type, n_embd_head_k);
const size_t row_v = ggml_row_size(qkv->type, n_embd_head_v);
const size_t row_full = qkv->nb[1];
const size_t k_off = row_k * n_head_l;
const size_t v_off = k_off + row_k * n_head_kv_l;
ggml_tensor * Qcur = ggml_view_3d(ctx0, qkv, n_embd_head_k, n_head_l, n_tokens, row_k, row_full, 0);
ggml_tensor * Kcur = ggml_view_3d(ctx0, qkv, n_embd_head_k, n_head_kv_l, n_tokens, row_k, row_full, k_off);
ggml_tensor * Vcur = ggml_view_3d(ctx0, qkv, n_embd_head_v, n_head_kv_l, n_tokens, row_v, row_full, v_off);
Qcur = ggml_rope_ext(
ctx0, Qcur, inp_pos, nullptr,
n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
ext_factor, attn_factor, beta_fast, beta_slow);
Kcur = ggml_rope_ext(
ctx0, Kcur, inp_pos, nullptr,
n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
ext_factor, attn_factor, beta_fast, beta_slow);
cb(Qcur, "mtp_Qcur", il);
cb(Kcur, "mtp_Kcur", il);
cb(Vcur, "mtp_Vcur", il);
cur = build_attn(inp_attn,
layer.wo, nullptr, layer.wo_s,
Qcur, Kcur, Vcur, nullptr, layer.attn_sinks, nullptr,
1.0f / sqrtf(float(n_embd_head_k)), il);
cb(cur, "mtp_attn_out", il);
if (v_scale) {
cur = ggml_scale(ctx0, cur, v_scale);
cb(cur, "mtp_attn_out_scaled", il);
}
ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
cb(ffn_inp, "mtp_ffn_inp", il);
cur = build_norm(ffn_inp, layer.ffn_norm, nullptr, LLM_NORM_RMS, il);
cb(cur, "mtp_ffn_norm", il);
GGML_ASSERT(layer.ffn_gate && layer.ffn_down && layer.ffn_up && "MIMO2 MTP requires dense FFN tensors");
cur = build_ffn(cur,
layer.ffn_up, layer.ffn_up_b, nullptr,
layer.ffn_gate, layer.ffn_gate_b, nullptr,
layer.ffn_down, layer.ffn_down_b, nullptr,
nullptr,
LLM_FFN_SILU, LLM_FFN_PAR, il);
cb(cur, "mtp_ffn_out", il);
cur = ggml_add(ctx0, cur, ffn_inp);
cb(cur, "mtp_post_ffn", il);
cur = ggml_get_rows(ctx0, cur, inp_out_ids);
cb(cur, "h_nextn", -1);
res->t_h_nextn = cur;
ggml_tensor * head_norm_w = layer.nextn.shared_head_norm
? layer.nextn.shared_head_norm
: (layer.layer_out_norm ? layer.layer_out_norm : model.output_norm);
GGML_ASSERT(head_norm_w && "MIMO2 MTP missing head norm fallback");
cur = build_norm(cur, head_norm_w, nullptr, LLM_NORM_RMS, -1);
cb(cur, "mtp_shared_head_norm", -1);
ggml_tensor * head_w = layer.nextn.shared_head_head ? layer.nextn.shared_head_head : model.output;
ggml_tensor * head_s = layer.nextn.shared_head_head ? layer.nextn.shared_head_head_s : model.output_s;
GGML_ASSERT(head_w && "MIMO2 MTP missing LM head fallback");
cur = build_lora_mm(head_w, cur, head_s);
cb(cur, "result_output", -1);
res->t_logits = cur;
ggml_build_forward_expand(gf, cur);
}
+4
View File
@@ -2127,6 +2127,10 @@ struct llama_model_mimo2 : public llama_model_base {
graph(const llama_model & model, const llm_graph_params & params);
};
struct graph_mtp : public llm_graph_context {
graph_mtp(const llama_model & model, const llm_graph_params & params);
};
std::unique_ptr<llm_graph_context> build_arch_graph(const llm_graph_params & params) const override;
};
+3
View File
@@ -278,6 +278,9 @@ set_tests_properties(test-state-restore-fragmented PROPERTIES FIXTURES_REQUIRED
llama_build_and_test(test-save-load-state.cpp LABEL "model" ARGS -m "${MODEL_DEST}")
set_tests_properties(test-save-load-state PROPERTIES FIXTURES_REQUIRED test-download-model)
if (APPLE)
llama_build(test-rset-release.cpp get-model.cpp)
endif()
if (NOT GGML_BACKEND_DL)
# these tests use the backends directly and cannot be built with dynamic loading
llama_build_and_test(test-barrier.cpp)
+7 -3
View File
@@ -1350,18 +1350,22 @@ struct test_case {
// check if the backends support the ops
bool supported = true;
std::string unsupported_str;
for (ggml_backend_t backend : {backend1, backend2}) {
for (ggml_tensor * t = ggml_get_first_tensor(ctx.get()); t != NULL; t = ggml_get_next_tensor(ctx.get(), t)) {
if (!ggml_backend_supports_op(backend, t)) {
supported = false;
break;
if (unsupported_str.empty()) {
unsupported_str = std::string(ggml_backend_name(backend));
} else {
unsupported_str += ", " + std::string(ggml_backend_name(backend));
}
}
}
}
if (!supported) {
// Create test result for unsupported operation
test_result result(ggml_backend_name(backend1), current_op_name, vars(), "test",
test_result result(unsupported_str, current_op_name, vars(), "test",
false, false, "not supported");
print_test_result_locked(output_printer, result);
+53
View File
@@ -0,0 +1,53 @@
// ref: https://github.com/ggml-org/llama.cpp/issues/25937
// only works reliably when run with a large model that occupies 3GB+ of wired memory
// thus, this test is not run by default
// example model to run with: google/gemma-4-E4B-it-qat-q4_0-gguf
#include <cstdint>
#include <mach/mach.h>
#include <mach/mach_host.h>
#include <unistd.h>
#include "llama.h"
#include "get-model.h"
static uint64_t wired_memory() {
vm_statistics64_data_t vmstat;
mach_msg_type_number_t count = HOST_VM_INFO64_COUNT;
if (host_statistics64(mach_host_self(), HOST_VM_INFO64, (host_info64_t)&vmstat, &count) != KERN_SUCCESS) {
return UINT64_MAX;
}
return static_cast<uint64_t>(vmstat.wire_count) * vm_kernel_page_size;
}
int main(int argc, char ** argv) {
auto * model_path = get_model_or_exit(argc, argv);
llama_backend_init();
const uint64_t wired_initial = wired_memory();
llama_model_params params = llama_model_default_params();
params.load_mode = LLAMA_LOAD_MODE_NONE;
struct llama_model* model = llama_model_load_from_file(model_path, params);
const uint64_t wired_loaded = wired_memory();
const uint64_t wired_delta = wired_loaded - wired_initial;
// system memory fluctuates, so we need to allocate enough to reliably detect the release
GGML_ASSERT(wired_delta > 2'000'000'000); // 2GB
llama_model_free(model);
const uint64_t t_start_ms = ggml_time_ms();
// expect most of the allocated memory to be released within 10 seconds
// we allow for some tolerance due to system-wide memory fluctuations
while (wired_memory() > wired_loaded - 0.75 * wired_delta) {
GGML_ASSERT(ggml_time_ms() - t_start_ms < 10'000);
usleep(100'000); // 100ms
}
llama_backend_free();
return 0;
}
+12 -7
View File
@@ -1537,7 +1537,7 @@ private:
// find the slot that has at least n% prompt similarity
if (slot_prompt_similarity != 0.0f) {
float sim_best = 0;
float f_sim_best = 0;
for (server_slot & slot : slots) {
if (task.id_slot != -1 && slot.id != task.id_slot) {
@@ -1546,6 +1546,7 @@ private:
// skip the slot if it is not available
if (slot.is_processing()) {
SLT_TRC(slot, " - skipping, is_processing = %d\n", slot.is_processing());
continue;
}
@@ -1553,26 +1554,30 @@ private:
// skip the slot if it does not contains cached tokens
if (tokens.empty()) {
SLT_TRC(slot, "%s", " - skipping, slot is empty\n");
continue;
}
// fraction of the Longest Common Prefix length with respect to the input prompt length
const float sim_cur = float(tokens.get_common_prefix(task.tokens)) / task.tokens.size();
const size_t lcp_len = tokens.get_common_prefix(task.tokens);
const float f_sim_cur = float(lcp_len) / task.tokens.size();
SLT_TRC(slot, " - checking sim = %.3f (%zu/%zu) > %.3f\n", f_sim_cur, lcp_len, task.tokens.size(), slot_prompt_similarity);
// select the current slot if the criteria match
if (sim_cur > sim_best && sim_cur > slot_prompt_similarity) {
sim_best = sim_cur;
if (f_sim_cur > f_sim_best && f_sim_cur > slot_prompt_similarity) {
f_sim_best = f_sim_cur;
ret = &slot;
}
}
if (ret != nullptr) {
const float f_keep = (sim_best*task.tokens.size()) / ret->prompt.tokens.size();
const float f_keep = (f_sim_best*task.tokens.size()) / ret->prompt.tokens.size();
if (task.id_slot == -1) {
SLT_INF(*ret, "selected slot by LCP similarity, sim_best = %.3f (> %.3f thold), f_keep = %.3f\n",
sim_best, slot_prompt_similarity, f_keep);
SLT_INF(*ret, "selected slot by LCP similarity, f_sim_best = %.3f (> %.3f thold), f_keep = %.3f\n",
f_sim_best, slot_prompt_similarity, f_keep);
}
// if we are about to lose a large portion of the existing context - save it in the prompt cache
+7 -7
View File
@@ -1742,9 +1742,9 @@ bool server_prompt_cache::load(server_prompt & prompt, const server_tokens & tok
const int lcp_best = prompt.tokens.get_common_prefix(tokens_new);
float f_keep_best = prompt.tokens.size() > 0 ? float(lcp_best) / prompt.tokens.size() : -1.0f; // empty slot: any cache entry wins
float sim_best = float(lcp_best) / tokens_new.size();
float f_sim_best = float(lcp_best) / tokens_new.size();
SRV_TRC(" - looking for better prompt, base f_keep = %.3f, sim = %.3f\n", f_keep_best, sim_best);
SRV_TRC(" - looking for better prompt, base f_keep = %.3f, f_sim = %.3f\n", f_keep_best, f_sim_best);
auto it_best = states.end();
@@ -1753,25 +1753,25 @@ bool server_prompt_cache::load(server_prompt & prompt, const server_tokens & tok
const int lcp_cur = it->prompt.tokens.get_common_prefix(tokens_new);
const float f_keep_cur = float(lcp_cur) / it->prompt.tokens.size();
const float sim_cur = float(lcp_cur) / tokens_new.size();
const float f_sim_cur = float(lcp_cur) / tokens_new.size();
SRV_TRC(" - prompt with length %7zu, lcp = %7d, f_keep = %.3f, sim = %.3f\n", it->prompt.tokens.size(), lcp_cur, f_keep_cur, sim_cur);
SRV_TRC(" - prompt with length %7zu, lcp = %7d, f_keep = %.3f, f_sim = %.3f\n", it->prompt.tokens.size(), lcp_cur, f_keep_cur, f_sim_cur);
// don't trash large prompts
if (f_keep_cur < 0.25f) {
continue;
}
if (f_keep_best < f_keep_cur && sim_best < sim_cur) {
if (f_keep_best < f_keep_cur && f_sim_best < f_sim_cur) {
f_keep_best = f_keep_cur;
sim_best = sim_cur;
f_sim_best = f_sim_cur;
it_best = it;
}
}
if (it_best != states.end()) {
SRV_TRC(" - found better prompt with f_keep = %.3f, sim = %.3f\n", f_keep_best, sim_best);
SRV_TRC(" - found better prompt with f_keep = %.3f, f_sim = %.3f\n", f_keep_best, f_sim_best);
{
auto & data = it_best->data.main;
@@ -48,6 +48,9 @@
}: Props = $props();
let dropdownOpen = $state(false);
// The system message action moves focus to the message editor, so the menu
// must not restore focus to the trigger on close
let suppressCloseAutoFocus = false;
function handleMcpSettingsClick() {
dropdownOpen = false;
@@ -96,7 +99,16 @@
</Tooltip.Content>
</Tooltip.Root>
<DropdownMenu.Content align="start" class="w-52">
<DropdownMenu.Content
align="start"
class="w-52"
onCloseAutoFocus={(e) => {
if (suppressCloseAutoFocus) {
suppressCloseAutoFocus = false;
e.preventDefault();
}
}}
>
<ChatFormActionAddReasoningSubmenu />
<DropdownMenu.Separator />
@@ -148,7 +160,10 @@
<DropdownMenu.Item
class="flex cursor-pointer items-center gap-2"
onclick={onSystemPromptClick}
onclick={() => {
suppressCloseAutoFocus = true;
onSystemPromptClick?.();
}}
>
<MessageSquare class={ICON_CLASS_DEFAULT} />
@@ -2,6 +2,7 @@
import { goto } from '$app/navigation';
import { getChatActionsContext, setMessageEditContext } from '$lib/contexts';
import { chatStore, pendingEditMessageId } from '$lib/stores/chat.svelte';
import { isMobile } from '$lib/stores/viewport.svelte';
import { conversationsStore } from '$lib/stores/conversations.svelte';
import { DatabaseService } from '$lib/services/database.service';
import { SYSTEM_MESSAGE_PLACEHOLDER } from '$lib/constants';
@@ -46,7 +47,14 @@
assistantMessages: number;
messageTypes: string[];
} | null>(null);
let editedContent = $derived(message.content);
// The system message placeholder must never surface as editable content; keeping
// it in the derived (not just in handleEdit) guards against prop invalidation
// reverting the override while editing
let editedContent = $derived(
message.role === MessageRole.SYSTEM && message.content === SYSTEM_MESSAGE_PLACEHOLDER
? ''
: message.content
);
let rawEditContent = $derived.by(() => {
if (message.role !== MessageRole.ASSISTANT) return undefined;
@@ -265,6 +273,12 @@
chatActions.navigateToSibling(siblingId);
}
// After the system message flow ends, hand focus to the main chat form
function focusMainChatForm() {
if (isMobile.current) return;
document.querySelector<HTMLTextAreaElement>('.chat-screen-form-wrapper textarea')?.focus();
}
async function handleSaveEdit() {
if (message.role === MessageRole.SYSTEM) {
// System messages: update in place without branching
@@ -276,6 +290,8 @@
isEditing = false;
if (conversationDeleted) {
goto(ROUTES.START);
} else {
focusMainChatForm();
}
return;
}
@@ -285,6 +301,7 @@
if (index !== -1) {
conversationsStore.updateMessageAtIndex(index, { content: newContent });
}
focusMainChatForm();
} else if (message.role === MessageRole.USER) {
const finalExtras = await getMergedExtras();
chatActions.editWithBranching(message, editedContent.trim(), finalExtras);
@@ -106,15 +106,23 @@
onFileRemove?.(fileId);
}
// Auto-focus must not steal focus already claimed elsewhere (e.g. the system
// message editor opened just before a navigation)
function focusFormUnlessCaptured() {
const active = document.activeElement;
if (active instanceof HTMLTextAreaElement || active instanceof HTMLInputElement) return;
chatFormRef?.focus();
}
onMount(() => {
if (!isMobile.current) {
setTimeout(() => chatFormRef?.focus(), 100);
setTimeout(focusFormUnlessCaptured, 100);
}
});
afterNavigate((navigation) => {
if (navigation?.from != null && !isMobile.current) {
setTimeout(() => chatFormRef?.focus(), 100);
setTimeout(focusFormUnlessCaptured, 100);
}
});
@@ -127,7 +135,7 @@
$effect(() => {
if (previousIsLoading && !isLoading) {
setTimeout(() => chatFormRef?.focus(), 10);
setTimeout(focusFormUnlessCaptured, 10);
}
previousIsLoading = isLoading;
@@ -11,7 +11,7 @@
<div
class={[
'pointer-events-none mb-4 hidden px-4 text-center text-balance',
isEmpty && 'mb-[calc(50dvh-8rem)] md:mb-6 pointer-events-auto block!'
isEmpty && 'mb-[calc(50dvh-8rem)] md:mb-8 pointer-events-auto block!'
]}
>
<h1 class="mb-2 text-2xl font-semibold tracking-tight md:text-3xl">Hello there</h1>
+31 -26
View File
@@ -31,14 +31,19 @@ export class DatabaseService {
* Creates a new conversation.
*
* @param name - Name of the conversation
* @param fields - Optional extra fields (e.g. reasoningEffort)
* @returns The created conversation
*/
static async createConversation(name: string): Promise<DatabaseConversation> {
static async createConversation(
name: string,
fields?: Partial<Omit<DatabaseConversation, 'id' | 'name' | 'lastModified'>>
): Promise<DatabaseConversation> {
const conversation: DatabaseConversation = {
id: uuid(),
name,
lastModified: Date.now(),
currNode: ''
currNode: '',
...fields
};
await db[IDXDB_TABLES.conversations].add(conversation);
@@ -137,7 +142,7 @@ export class DatabaseService {
* @param systemPrompt - The system prompt content (must be non-empty)
* @param parentId - Parent message ID (typically the root message)
* @returns The created system message
* @throws Error if systemPrompt is empty
* @throws Error if systemPrompt is empty or the parent message does not exist
*/
static async createSystemMessage(
convId: string,
@@ -149,27 +154,30 @@ export class DatabaseService {
throw new Error('Cannot create system message with empty content');
}
const systemMessage: DatabaseMessage = {
id: uuid(),
convId,
type: MessageRole.SYSTEM,
timestamp: Date.now(),
role: MessageRole.SYSTEM,
content: trimmedPrompt,
parent: parentId,
children: []
};
return await db.transaction('rw', db[IDXDB_TABLES.messages], async () => {
const parentMessage = await db[IDXDB_TABLES.messages].get(parentId);
if (!parentMessage) {
throw new Error(`Parent message ${parentId} not found`);
}
await db[IDXDB_TABLES.messages].add(systemMessage);
const systemMessage: DatabaseMessage = {
id: uuid(),
convId,
type: MessageRole.SYSTEM,
timestamp: Date.now(),
role: MessageRole.SYSTEM,
content: trimmedPrompt,
parent: parentId,
children: []
};
const parentMessage = await db[IDXDB_TABLES.messages].get(parentId);
if (parentMessage) {
await db[IDXDB_TABLES.messages].add(systemMessage);
await db[IDXDB_TABLES.messages].update(parentId, {
children: [...parentMessage.children, systemMessage.id]
});
}
return systemMessage;
return systemMessage;
});
}
/**
@@ -442,7 +450,8 @@ export class DatabaseService {
}
/**
* Updates a conversation.
* Updates a conversation. `lastModified` is never stamped implicitly;
* pass it in `updates` to bump the conversation in recency ordering.
*
* @param id - Conversation ID
* @param updates - Partial updates to apply
@@ -452,10 +461,7 @@ export class DatabaseService {
id: string,
updates: Partial<Omit<DatabaseConversation, 'id'>>
): Promise<void> {
await db[IDXDB_TABLES.conversations].update(id, {
...updates,
lastModified: Date.now()
});
await db[IDXDB_TABLES.conversations].update(id, updates);
}
/**
@@ -473,7 +479,7 @@ export class DatabaseService {
* @returns The new pinned status
*/
static async toggleConversationPin(id: string): Promise<boolean> {
const conversation = await db.conversations.get(id);
const conversation = await db[IDXDB_TABLES.conversations].get(id);
if (!conversation) {
throw new Error(`Conversation ${id} not found`);
}
@@ -497,7 +503,6 @@ export class DatabaseService {
const result = new Map<string, boolean>();
if (cleanIds.length === 0) return result;
const now = Date.now();
await db.transaction('rw', db[IDXDB_TABLES.conversations], async () => {
const convs = await db[IDXDB_TABLES.conversations].bulkGet(cleanIds);
const updates: DatabaseConversation[] = [];
@@ -505,7 +510,7 @@ export class DatabaseService {
const conv = convs[i];
if (!conv) continue;
const newPinned = !conv.pinned;
updates.push({ ...conv, pinned: newPinned, lastModified: now });
updates.push({ ...conv, pinned: newPinned });
result.set(cleanIds[i], newPinned);
}
if (updates.length === 0) return;
+4 -3
View File
@@ -1658,7 +1658,8 @@ class ChatStore {
generateConversationTitle(newContent, Boolean(config().titleGenerationUseFirstLine))
);
const messagesToRemove = conversationsStore.activeMessages.slice(messageIndex + 1);
for (const message of messagesToRemove) await DatabaseService.deleteMessage(message.id);
if (messagesToRemove.length > 0)
await DatabaseService.deleteMessageCascading(activeConv.id, messagesToRemove[0].id);
conversationsStore.sliceActiveMessages(messageIndex + 1);
conversationsStore.updateConversationTimestamp();
this.setChatLoading(activeConv.id, true);
@@ -1690,7 +1691,7 @@ class ChatStore {
const { index: messageIndex } = result;
try {
const messagesToRemove = conversationsStore.activeMessages.slice(messageIndex);
for (const message of messagesToRemove) await DatabaseService.deleteMessage(message.id);
await DatabaseService.deleteMessageCascading(activeConv.id, messagesToRemove[0].id);
conversationsStore.sliceActiveMessages(messageIndex);
conversationsStore.updateConversationTimestamp();
this.setChatLoading(activeConv.id, true);
@@ -2037,7 +2038,7 @@ class ChatStore {
timings
});
conversationsStore.updateConversationTimestamp();
conversationsStore.updateConversationTimestamp(msg.convId);
this.setChatLoading(msg.convId, false);
this.clearChatStreaming(msg.convId);
+45 -31
View File
@@ -111,6 +111,9 @@ class ConversationsStore {
| ((messageId: string, updates: Partial<DatabaseMessage>) => void)
| null = null;
/** In-flight init run; shared by concurrent callers, reset on failure to allow retry */
private initPromise: Promise<void> | null = null;
/**
*
*
@@ -121,19 +124,25 @@ class ConversationsStore {
/**
* Initialize the store by loading conversations from database.
* Must be called once after app startup.
* Safe to call multiple times: concurrent callers share a single run,
* and a failed run can be retried by calling again.
*/
async init(): Promise<void> {
if (!browser) return;
if (this.isInitialized) return;
init(): Promise<void> {
if (!browser) return Promise.resolve();
if (this.initPromise) return this.initPromise;
try {
await MigrationService.runAllMigrations();
await this.loadConversations();
this.isInitialized = true;
} catch (error) {
console.error('Failed to initialize conversations:', error);
}
this.initPromise = (async () => {
try {
await MigrationService.runAllMigrations();
await this.loadConversations();
this.isInitialized = true;
} catch (error) {
console.error('Failed to initialize conversations:', error);
this.initPromise = null;
}
})();
return this.initPromise;
}
/**
@@ -237,15 +246,11 @@ class ConversationsStore {
*/
async createConversation(name?: string): Promise<string> {
const conversationName = name || `Chat ${new Date().toLocaleString()}`;
const conversation = await DatabaseService.createConversation(conversationName);
// No MCP override list is seeded: getAllMcpServerOverrides resolves
// servers without a per-conversation override to `mcpServers[i].enabled`,
// and only explicit toggles are stored on the conversation.
// Inherit the global reasoning default into the new conversation
conversation.reasoningEffort = this.pendingReasoningEffort;
await DatabaseService.updateConversation(conversation.id, {
const conversation = await DatabaseService.createConversation(conversationName, {
reasoningEffort: this.pendingReasoningEffort
});
@@ -358,10 +363,7 @@ class ConversationsStore {
async deleteAll(): Promise<void> {
try {
const allConversations = await DatabaseService.getAllConversations();
for (const conv of allConversations) {
await DatabaseService.deleteConversation(conv.id);
}
await DatabaseService.bulkDeleteConversations(allConversations.map((c) => c.id));
this.clearActiveConversation();
this.conversations = [];
@@ -412,7 +414,9 @@ class ConversationsStore {
}
toast.success(
convIds.length === 1 ? 'Conversation deleted' : `${convIds.length} conversations deleted`
idsToRemove.size === 1
? 'Conversation deleted'
: `${idsToRemove.size} conversations deleted`
);
} catch (error) {
console.error('Failed to bulk delete conversations:', error);
@@ -443,7 +447,6 @@ class ConversationsStore {
const newPinned = updates.get(this.conversations[i].id);
if (newPinned !== undefined) this.conversations[i].pinned = newPinned;
}
this.conversations = [...this.conversations];
toast.success(
convIds.length === 1
@@ -552,7 +555,6 @@ class ConversationsStore {
if (convIndex !== -1) {
this.conversations[convIndex].name = name;
this.conversations = [...this.conversations];
}
if (this.activeConversation?.id === convId) {
@@ -576,7 +578,6 @@ class ConversationsStore {
if (convIndex !== -1) {
this.conversations[convIndex].pinned = newPinnedState;
this.conversations = [...this.conversations];
}
if (this.activeConversation?.id === convId) {
@@ -591,18 +592,33 @@ class ConversationsStore {
}
/**
* Updates conversation lastModified timestamp and moves it to top of list
* Marks a conversation as recently active: stamps lastModified (persisted)
* and moves it to the top of the list. Only message-activity flows call
* this; metadata updates (rename, pin, settings) do not.
*
* @param convId - Conversation that produced the activity, defaults to the active one
*/
updateConversationTimestamp(): void {
if (!this.activeConversation) return;
updateConversationTimestamp(convId?: string): void {
const targetId = convId ?? this.activeConversation?.id;
if (!targetId) return;
const chatIndex = this.conversations.findIndex((c) => c.id === this.activeConversation!.id);
const now = Date.now();
const chatIndex = this.conversations.findIndex((c) => c.id === targetId);
if (chatIndex !== -1) {
this.conversations[chatIndex].lastModified = Date.now();
this.conversations[chatIndex].lastModified = now;
const updatedConv = this.conversations.splice(chatIndex, 1)[0];
this.conversations = [updatedConv, ...this.conversations];
}
if (this.activeConversation?.id === targetId) {
this.activeConversation = { ...this.activeConversation, lastModified: now };
}
DatabaseService.updateConversation(targetId, { lastModified: now }).catch((error) =>
console.error('Failed to update conversation timestamp:', error)
);
}
/**
@@ -773,7 +789,6 @@ class ConversationsStore {
if (convIndex !== -1) {
this.conversations[convIndex].mcpServerOverrides =
newOverrides.length > 0 ? newOverrides : undefined;
this.conversations = [...this.conversations];
}
}
@@ -837,7 +852,6 @@ class ConversationsStore {
const convIndex = this.conversations.findIndex((c) => c.id === this.activeConversation!.id);
if (convIndex !== -1) {
this.conversations[convIndex].reasoningEffort = effort;
this.conversations = [...this.conversations];
}
}
-364
View File
@@ -1,364 +0,0 @@
/**
* @deprecated Legacy migration utility remove at some point in the future once all users have migrated to the new structured agentic message format.
*
* Converts old marker-based agentic messages to the new structured format
* with separate messages per turn.
*
* Old format: Single assistant message with markers in content:
* <<<reasoning_content_start>>>...<<<reasoning_content_end>>>
* <<<AGENTIC_TOOL_CALL_START>>>...<<<AGENTIC_TOOL_CALL_END>>>
*
* New format: Separate messages per turn:
* - assistant (content + reasoningContent + toolCalls)
* - tool (toolCallId + content)
* - assistant (next turn)
* - ...
*/
import { LEGACY_AGENTIC_REGEX, LEGACY_REASONING_TAGS } from '$lib/constants';
import { DatabaseService } from '$lib/services/database.service';
import { MessageRole, MessageType } from '$lib/enums';
import type { DatabaseMessage } from '$lib/types/database';
const MIGRATION_DONE_KEY = 'llama-ui-migration-v2-done';
/** @deprecated Use {@link MIGRATION_DONE_KEY} instead */
const DEPRECATED_MIGRATION_DONE_KEY = 'llama-webui-migration-v2-done';
/**
* @deprecated Part of legacy migration remove with the migration module.
* Check if migration has been performed.
*/
export function isMigrationNeeded(): boolean {
try {
// Check new key first, fall back to deprecated old key
if (localStorage.getItem(MIGRATION_DONE_KEY)) return false;
if (localStorage.getItem(DEPRECATED_MIGRATION_DONE_KEY)) {
// Migrate to new key
try {
localStorage.setItem(MIGRATION_DONE_KEY, String(Date.now()));
localStorage.removeItem(DEPRECATED_MIGRATION_DONE_KEY);
} catch {
// Ignore storage errors
}
return false;
}
return true;
} catch {
return false;
}
}
/**
* Mark migration as done.
*/
function markMigrationDone(): void {
try {
localStorage.setItem(MIGRATION_DONE_KEY, String(Date.now()));
} catch {
// Ignore localStorage errors
}
}
/**
* Check if a message has legacy markers in its content.
*/
function hasLegacyMarkers(message: DatabaseMessage): boolean {
if (!message.content) return false;
return LEGACY_AGENTIC_REGEX.HAS_LEGACY_MARKERS.test(message.content);
}
/**
* Extract reasoning content from legacy marker format.
*/
function extractLegacyReasoning(content: string): { reasoning: string; cleanContent: string } {
let reasoning = '';
let cleanContent = content;
// Extract all reasoning blocks
const re = new RegExp(LEGACY_AGENTIC_REGEX.REASONING_EXTRACT.source, 'g');
let match;
while ((match = re.exec(content)) !== null) {
reasoning += match[1];
}
// Remove reasoning tags from content
cleanContent = cleanContent
.replace(new RegExp(LEGACY_AGENTIC_REGEX.REASONING_BLOCK.source, 'g'), '')
.replace(LEGACY_AGENTIC_REGEX.REASONING_OPEN, '');
return { reasoning, cleanContent };
}
/**
* Parse legacy content with tool call markers into structured turns.
*/
interface ParsedTurn {
textBefore: string;
toolCalls: Array<{
name: string;
args: string;
result: string;
}>;
}
function parseLegacyToolCalls(content: string): ParsedTurn[] {
const turns: ParsedTurn[] = [];
const regex = new RegExp(LEGACY_AGENTIC_REGEX.COMPLETED_TOOL_CALL.source, 'g');
let lastIndex = 0;
let currentTurn: ParsedTurn = { textBefore: '', toolCalls: [] };
let match;
while ((match = regex.exec(content)) !== null) {
const textBefore = content.slice(lastIndex, match.index).trim();
// If there's text between tool calls and we already have tool calls,
// that means a new turn started (text after tool results = new LLM turn)
if (textBefore && currentTurn.toolCalls.length > 0) {
turns.push(currentTurn);
currentTurn = { textBefore, toolCalls: [] };
} else if (textBefore && currentTurn.toolCalls.length === 0) {
currentTurn.textBefore = textBefore;
}
currentTurn.toolCalls.push({
name: match[1],
args: match[2],
result: match[3].replace(/^\n+|\n+$/g, '')
});
lastIndex = match.index + match[0].length;
}
// Any remaining text after the last tool call
const remainingText = content.slice(lastIndex).trim();
if (currentTurn.toolCalls.length > 0) {
turns.push(currentTurn);
}
// If there's text after all tool calls, it's the final assistant response
if (remainingText) {
// Remove any partial/open markers
const cleanRemaining = remainingText
.replace(LEGACY_AGENTIC_REGEX.AGENTIC_TOOL_CALL_OPEN, '')
.trim();
if (cleanRemaining) {
turns.push({ textBefore: cleanRemaining, toolCalls: [] });
}
}
// If no tool calls found at all, return the original content as a single turn
if (turns.length === 0) {
turns.push({ textBefore: content.trim(), toolCalls: [] });
}
return turns;
}
/**
* Migrate a single conversation's messages from legacy format to new format.
*/
async function migrateConversation(convId: string): Promise<number> {
const allMessages = await DatabaseService.getConversationMessages(convId);
let migratedCount = 0;
for (const message of allMessages) {
if (message.role !== MessageRole.ASSISTANT) continue;
if (!hasLegacyMarkers(message)) {
// Still check for reasoning-only markers (no tool calls)
if (message.content?.includes(LEGACY_REASONING_TAGS.START)) {
const { reasoning, cleanContent } = extractLegacyReasoning(message.content);
await DatabaseService.updateMessage(message.id, {
content: cleanContent.trim(),
reasoningContent: reasoning || undefined
});
migratedCount++;
}
continue;
}
// Has agentic markers - full migration needed
const { reasoning, cleanContent } = extractLegacyReasoning(message.content);
const turns = parseLegacyToolCalls(cleanContent);
// Parse existing toolCalls JSON to try to match IDs
let existingToolCalls: Array<{
id: string;
function?: { name: string; arguments: string };
}> = [];
if (message.toolCalls) {
try {
existingToolCalls = JSON.parse(message.toolCalls);
} catch {
// Ignore
}
}
// First turn uses the existing message
const firstTurn = turns[0];
if (!firstTurn) continue;
// Match tool calls from the first turn to existing IDs
const firstTurnToolCalls = firstTurn.toolCalls.map((tc, i) => {
const existing =
existingToolCalls.find((e) => e.function?.name === tc.name) || existingToolCalls[i];
return {
id: existing?.id || `legacy_tool_${i}`,
type: 'function' as const,
function: { name: tc.name, arguments: tc.args }
};
});
// Update the existing message for the first turn
await DatabaseService.updateMessage(message.id, {
content: firstTurn.textBefore,
reasoningContent: reasoning || undefined,
toolCalls: firstTurnToolCalls.length > 0 ? JSON.stringify(firstTurnToolCalls) : ''
});
let currentParentId = message.id;
let toolCallIdCounter = existingToolCalls.length;
// Create tool result messages for the first turn
for (let i = 0; i < firstTurn.toolCalls.length; i++) {
const tc = firstTurn.toolCalls[i];
const toolCallId = firstTurnToolCalls[i]?.id || `legacy_tool_${i}`;
const toolMsg = await DatabaseService.createMessageBranch(
{
convId,
type: MessageType.TEXT,
role: MessageRole.TOOL,
content: tc.result,
toolCallId,
timestamp: message.timestamp + i + 1,
toolCalls: '',
children: []
},
currentParentId
);
currentParentId = toolMsg.id;
}
// Create messages for subsequent turns
for (let turnIdx = 1; turnIdx < turns.length; turnIdx++) {
const turn = turns[turnIdx];
const turnToolCalls = turn.toolCalls.map((tc, i) => {
const idx = toolCallIdCounter + i;
const existing = existingToolCalls[idx];
return {
id: existing?.id || `legacy_tool_${idx}`,
type: 'function' as const,
function: { name: tc.name, arguments: tc.args }
};
});
toolCallIdCounter += turn.toolCalls.length;
// Create assistant message for this turn
const assistantMsg = await DatabaseService.createMessageBranch(
{
convId,
type: MessageType.TEXT,
role: MessageRole.ASSISTANT,
content: turn.textBefore,
timestamp: message.timestamp + turnIdx * 100,
toolCalls: turnToolCalls.length > 0 ? JSON.stringify(turnToolCalls) : '',
children: [],
model: message.model
},
currentParentId
);
currentParentId = assistantMsg.id;
// Create tool result messages for this turn
for (let i = 0; i < turn.toolCalls.length; i++) {
const tc = turn.toolCalls[i];
const toolCallId = turnToolCalls[i]?.id || `legacy_tool_${toolCallIdCounter + i}`;
const toolMsg = await DatabaseService.createMessageBranch(
{
convId,
type: MessageType.TEXT,
role: MessageRole.TOOL,
content: tc.result,
toolCallId,
timestamp: message.timestamp + turnIdx * 100 + i + 1,
toolCalls: '',
children: []
},
currentParentId
);
currentParentId = toolMsg.id;
}
}
// Re-parent any children of the original message to the last created message
// (the original message's children list was the next user message or similar)
if (message.children.length > 0 && currentParentId !== message.id) {
for (const childId of message.children) {
// Skip children we just created (they were already properly parented)
const child = allMessages.find((m) => m.id === childId);
if (!child) continue;
// Only re-parent non-tool messages that were original children
if (child.role !== MessageRole.TOOL) {
await DatabaseService.updateMessage(childId, { parent: currentParentId });
// Add to new parent's children
const newParent = await DatabaseService.getConversationMessages(convId).then((msgs) =>
msgs.find((m) => m.id === currentParentId)
);
if (newParent && !newParent.children.includes(childId)) {
await DatabaseService.updateMessage(currentParentId, {
children: [...newParent.children, childId]
});
}
}
}
// Clear re-parented children from the original message
await DatabaseService.updateMessage(message.id, { children: [] });
}
migratedCount++;
}
return migratedCount;
}
/**
* @deprecated Part of legacy migration remove with the migration module.
* Run the full migration across all conversations.
* This should be called once at app startup if migration is needed.
*/
export async function runLegacyMigration(): Promise<void> {
if (!isMigrationNeeded()) return;
if (import.meta.env.DEV && import.meta.env.VITE_DEBUG)
console.log('[Migration] Starting legacy message format migration...');
try {
const conversations = await DatabaseService.getAllConversations();
let totalMigrated = 0;
for (const conv of conversations) {
const count = await migrateConversation(conv.id);
totalMigrated += count;
}
if (import.meta.env.DEV && import.meta.env.VITE_DEBUG) {
if (totalMigrated > 0) {
console.log(
`[Migration] Migrated ${totalMigrated} messages across ${conversations.length} conversations`
);
} else {
console.log('[Migration] No legacy messages found, marking as done');
}
}
markMigrationDone();
} catch (error) {
console.error('[Migration] Failed to migrate legacy messages:', error);
// Still mark as done to avoid infinite retry loops
markMigrationDone();
}
}
+1 -1
View File
@@ -41,7 +41,7 @@ if (LLAMA_BUILD_BORINGSSL)
set(FIPS OFF CACHE BOOL "Enable FIPS (BoringSSL)")
set(BORINGSSL_GIT "https://boringssl.googlesource.com/boringssl" CACHE STRING "BoringSSL git repository")
set(BORINGSSL_VERSION "0.20260713.0" CACHE STRING "BoringSSL version")
set(BORINGSSL_VERSION "0.20260728.0" CACHE STRING "BoringSSL version")
message(STATUS "Fetching BoringSSL version ${BORINGSSL_VERSION}")