llama_cpp_for_radxa_dragon_.../ggml
lnigam 7b8443ac78
ggml-cuda: add flash-attn support for DKQ=320/DV=256 with ncols2=32 (… (#22286)
* ggml-cuda: add flash-attn support for DKQ=320/DV=256 with ncols2=32 (GQA=32)

Adds MMA-f16 and tile kernel configs, dispatch logic, template instances,
and tile .cu file for Mistral Small 4 (head sizes 320/256), restricting to
ncols2=32 to support GQA ratio 32 only.

* Adding check to return BEST_FATTN_KERNEL_NONE in case GQA!=32

* Apply suggestions from code review

Address review comments

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Address review comments and making kernel config default to DQK=512, DV=512 instead of DQK=256,DV=256

* Fixed bug with sinks=1, with ncols=32, there are two warp-groups created but sinks index is same(0,...,15) for both the groups hence with sinks=1, output is not matching with CPU output. Added sink_base which will be base index for each warp_group (threadIdx.y / np)

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Update ggml/src/ggml-cuda/template-instances/generate_cu_files.py

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2026-04-28 21:37:35 +02:00
..
cmake ggml: backend-agnostic tensor parallelism (experimental) (#19378) 2026-04-09 16:42:19 +02:00
include CUDA: manage NCCL communicators in context (#21891) 2026-04-15 15:58:40 +02:00
src ggml-cuda: add flash-attn support for DKQ=320/DV=256 with ncols2=32 (… (#22286) 2026-04-28 21:37:35 +02:00
.gitignore
CMakeLists.txt HIP: flip GGML_HIP_GRAPHS to default on (#22254) 2026-04-23 02:34:31 +02:00