]> git.djapps.eu Git - pkg/ggml/sources/whisper.cpp/commit
AVX BF16 and single scale quant optimizations (llama/10212)
authorEve <redacted>
Fri, 15 Nov 2024 11:47:58 +0000 (11:47 +0000)
committerGeorgi Gerganov <redacted>
Wed, 20 Nov 2024 19:00:08 +0000 (21:00 +0200)
commit3216efef2eeb15f39752ffef838bb0010baa7f72
tree92b98b79d39d13ab7e3a89b0e2e97fb3e11b8458
parent2c0484ebf70f9dc407cd0ffc9d92df5acfcd139a
AVX BF16 and single scale quant optimizations (llama/10212)

* use 128 bit loads (i've tried 256->128 to death and its slower)

* double accumulator

* avx bf16 vec dot

* +3% q4_0 inference

* +7% tg +5% pp compared to master

* slower f16c version, kep for reference

* 256b version, also slow. i tried :)

* revert f16

* faster with madd

* split to functions

* Q8_0 and IQ4_NL, 5-7% faster

* fix potential overflow (performance reduced)

* 16 bit add for q4_0 only

* merge
ggml/src/ggml-cpu/ggml-cpu-quants.c
ggml/src/ggml-cpu/ggml-cpu.c