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llama : do not cap thread count when MoE on CPU (#5419)

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* Not capping thread count when MoE inference is running on CPU

* Whitespace
This commit is contained in:
Paul Tsochantaris
2024-02-09 10:48:06 +00:00
committed by GitHub
parent e4124c2477
commit e5ca3937c6
1 changed files with 3 additions and 1 deletions
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llama.cpp
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@@ -7285,7 +7285,9 @@ static int llama_decode_internal(
// TODO: this is mostly important for Apple Silicon where CBLAS is still performing very well // TODO: this is mostly important for Apple Silicon where CBLAS is still performing very well
// we still need some threads to process all non-mul_mat ops, but not too much to avoid interfering // we still need some threads to process all non-mul_mat ops, but not too much to avoid interfering
// with the BLAS calls. need a better solution // with the BLAS calls. need a better solution
if (n_tokens >= 32 && ggml_cpu_has_blas() && !ggml_cpu_has_gpublas()) { // MoE Special Case: This logic applies when hparams.n_expert == 0, i.e. the model is NOT an MoE model. When an MoE is
// being processed then Accelerate/BLAS will not be involved, so capping would limit performance.
if (n_tokens >= 32 && hparams.n_expert == 0 && ggml_cpu_has_blas() && !ggml_cpu_has_gpublas()) {
n_threads = std::min(4, n_threads); n_threads = std::min(4, n_threads);
} }