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metal : optimize Metal Tensor API usage for GGML_OP_MUL_MAT (#20962)

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* Optimize Metal Tensor API usage for matmul2d

Separates the Metal Tensor API (matmul2d) path in kernel_mul_mm into its own standalone kernel, gated by GGML_METAL_HAS_TENSOR.

The legacy simdgroup_matrix kernel is preserved under #else.

Previously both paths were interleaved via #ifdef blocks within a single kernel, forcing the tensor path to share the legacy kernel's data layout and threadgroup memory scheme. Splitting the kernel enabled memory and dispatch optimizations that weren't possible when the two paths shared code structure.

* cont : cleanup

* cont : cleanup

* cont : cleanup

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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Developer-Ecosystem-Engineering
2026-04-25 15:14:28 +03:00
committed by GitHub
co-authored by Georgi Gerganov
parent 9d34231bb8
commit d1649047a3
6 changed files with 189 additions and 109 deletions
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ggml/src/ggml-metal/ggml-metal-device.h
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@@ -102,6 +102,8 @@ ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev
void ggml_metal_library_free(ggml_metal_library_t lib);
ggml_metal_device_t ggml_metal_library_get_device(ggml_metal_library_t lib);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline (ggml_metal_library_t lib, const char * name);
struct ggml_metal_pipeline_with_params ggml_metal_library_compile_pipeline(ggml_metal_library_t lib, const char * base, const char * name, ggml_metal_cv_t cv);