Skip to content

Conversation

sirus20x6
Copy link
Contributor

Vectorizes the following functions in ggml.c on x86:
ggml_fp16_to_fp32_row: using F16C intrinsics.
ggml_fp32_to_fp16_row: using F16C intrinsics.
ggml_bf16_to_fp32_row: using AVX2 and AVX512F intrinsics.

Vectorized the following functions in ggml.c for improved performance on x86 architectures:
- ggml_fp16_to_fp32_row: using F16C intrinsics.
- ggml_fp32_to_fp16_row: using F16C intrinsics.
- ggml_bf16_to_fp32_row: using AVX2 and AVX512F intrinsics.

This change follows the existing pattern of using direct SIMD intrinsic checks in this file.
@github-actions github-actions bot added the ggml changes relating to the ggml tensor library for machine learning label Oct 15, 2025
ggerganov
ggerganov previously approved these changes Oct 15, 2025
@slaren
Copy link
Member

slaren commented Oct 15, 2025

The vectorized versions should be in the CPU backend. See #13107

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

ggml changes relating to the ggml tensor library for machine learning

Projects

None yet

Development

Successfully merging this pull request may close these issues.

3 participants