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PrismML-Eng
llama.cpp
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CUDA: fast, batch-invariant small-batch PTQ1_0 mat-vec (1.5x decode on Ampere)
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CUDA: fast, batch-invariant small-batch PTQ1_0 mat-vec (1.5x decode on Ampere)
#218
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Commits on Sep 22, 2026
Add: planar-transposed activation layout for the PTQ1_0 mat-vec path
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Add: dedicated PTQ1_0 mat-vec kernel with full lane utilization
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Test: add Bonsai 2 projection shapes to the mul_mat perf cases
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Add: GGML_CUDA_BATCH_INVARIANT for batch-invariant small-batch kernels
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Fix: use the mat-vec kernel for bf16 matrices under 64 rows at 2 to 8 columns
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Fix: keep GGML_CUDA_RESTRICT off the PTQ1_0 mat-vec kernel signature
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Docs: state the batch-invariance guarantee as 1 to 4 columns
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Fix: budget the PTQ1_0 mat-vec shared memory the launch will request
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Docs: scope the GGML_CUDA_BATCH_INVARIANT comment to the paths the flag changes
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Fix: cap the PTQ1_0 mat-vec at 4 columns and send 5 and above to the MMQ tile path
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Commits on Oct 10, 2026
Fix: wait on the PDL dependency in the PTQ1_0 mat-vec kernel before reading vy
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