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llama.cpp adds wide SYCL FWHT kernels for Intel GPUs
llama.cpp Releaseshigh confidence
Why it matters
- →Reduces computational complexity from O(n^2) to O(n log n) for large Hadamard transforms on Intel GPUs.
- →Enables efficient execution of block widths up to 8192, previously unsupported by narrow kernels.
- →Improves inference speed for llama.cpp users on SYCL hardware without requiring code changes.
llama.cpp has merged a pull request (#29243) adding Fast Walsh-Hadamard Transform (FWHT) kernels for SYCL block widths above 512. Previously, larger blocks fell back to O(n^2) dense GEMM operations; the new implementation supports widths of 640, 768, 1280, and powers of two up to 8192 using an efficient butterfly network with work-group local memory shuffling. The code was verified against a recursive-doubling Hadamard reference on Intel oneAPI DPC++ 2026.1, showing negligible error margins across single- and multi-row configurations. This update improves inference efficiency for Intel GPU users without requiring new hardware, addressing a specific performance bottleneck in the SYCL backend.
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Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1Llama.cpp Enhances OpenCL Flash Attention
llama.cpp Releases · June 28, 2026 · Same story
- 2llama.cpp b11046 adds OpenCL flash attention
llama.cpp Releases · September 19, 2026 · Same story
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Open the full story →llama.cpp b11059 optimizes Metal FWHT for Apple Silicon
2 developments
- Sep 20 · llama.cpp Releases
llama.cpp b11059 optimizes Metal FWHT for Apple Silicon - Sep 28 · llama.cpp Releases
llama.cpp adds wide SYCL FWHT kernels for Intel GPUs (This article)↳ llama.cpp adds wide SYCL FWHT kernels for Intel GPUs
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