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metal : clamp K extent in tensor API mat-mat kernel - #27450
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…ple of 32 The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a static K=32 tile to the matmul2d op on every iteration. On the last, partial K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the tensor, and the op reads those out-of-bounds elements (undefined behavior per the MSL specification, section 2.22.2). Depending on stale memory contents, this corrupted the result or produced NaN. Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range on every iteration (mirroring the tail handling of the MPP matmul2d examples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration). Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path. Assisted-by: pi:llama.cpp/Qwen3.8-27B
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Both mtmd + test-backend-ops pass on my machine with this fix |
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Awesome |
ggerganov
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August 20, 2026 17:24
therealkenc
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Aug 24, 2026
…ple of 32 (ggml-org#27450) The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a static K=32 tile to the matmul2d op on every iteration. On the last, partial K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the tensor, and the op reads those out-of-bounds elements (undefined behavior per the MSL specification, section 2.22.2). Depending on stale memory contents, this corrupted the result or produced NaN. Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range on every iteration (mirroring the tail handling of the MPP matmul2d examples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration). Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path. Assisted-by: pi:llama.cpp/Qwen3.8-27B
thecodacus
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Sep 7, 2026
…ple of 32 (ggml-org#27450) The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a static K=32 tile to the matmul2d op on every iteration. On the last, partial K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the tensor, and the op reads those out-of-bounds elements (undefined behavior per the MSL specification, section 2.22.2). Depending on stale memory contents, this corrupted the result or produced NaN. Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range on every iteration (mirroring the tail handling of the MPP matmul2d examples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration). Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path. Assisted-by: pi:llama.cpp/Qwen3.8-27B
zbrad
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Sep 10, 2026
…ple of 32 (ggml-org#27450) The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a static K=32 tile to the matmul2d op on every iteration. On the last, partial K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the tensor, and the op reads those out-of-bounds elements (undefined behavior per the MSL specification, section 2.22.2). Depending on stale memory contents, this corrupted the result or produced NaN. Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range on every iteration (mirroring the tail handling of the MPP matmul2d examples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration). Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path. Assisted-by: pi:llama.cpp/Qwen3.8-27B
pl752
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Sep 15, 2026
…ple of 32 (ggml-org#27450) The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a static K=32 tile to the matmul2d op on every iteration. On the last, partial K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the tensor, and the op reads those out-of-bounds elements (undefined behavior per the MSL specification, section 2.22.2). Depending on stale memory contents, this corrupted the result or produced NaN. Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range on every iteration (mirroring the tail handling of the MPP matmul2d examples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration). Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path. Assisted-by: pi:llama.cpp/Qwen3.8-27B
frostyautumnleaf
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Oct 5, 2026
…ple of 32 (ggml-org#27450) The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a static K=32 tile to the matmul2d op on every iteration. On the last, partial K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the tensor, and the op reads those out-of-bounds elements (undefined behavior per the MSL specification, section 2.22.2). Depending on stale memory contents, this corrupted the result or produced NaN. Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range on every iteration (mirroring the tail handling of the MPP matmul2d examples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration). Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path. Assisted-by: pi:llama.cpp/Qwen3.8-27B
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Overview
The Tensor API mat-mat path of
kernel_mul_mm(GGML_METAL_HAS_TENSOR) feeds a static K=32 tile to thematmul2dop on every K-loop iteration. When K is not a multiple of 32, the last, partial K tile extends past the K extent of the src1 tensor, and the op reads those out-of-bounds elements — undefined behavior per the MSL spec (section 2.22.2). Depending on stale arena memory contents, this silently corrupted results or produced NaN (e.g. #25652, K=588, M5).Fix the kernel itself: make the op use
dynamic_extentfor K, and clamp the K extent of both operand tensor views to the remaining valid K range (min(32, K - loop_k)) per iteration, so the op reads exactly the valid K range (mirroring the tail handling of the MPPmatmul2dexamples). On K-aligned inputs the clamp degenerates to the full 32-wide tile: the only difference from the static-K op is that the dynamic-K op derives K from the operand extents and edge-checks the tile against the tensor extents (a handful of integer ops per iteration).Also adds
test-backend-opsMUL_MAT cases with K not a multiple of 32 to exercise the unaligned K path.Additional information
has_tensor): fullMUL_MATsuite 1161/1161; unaligned K cases (k=65/80/588, f16/f16, f16/f32, f32/f32, batched) pass.Requirements