Q8_K_R8: Fastest quantized matrix multiplications (#141)

* q8_k_r8: fastest matrix multiplication known to human kind

We get PP-512(LLaMA-3.1-8B) = 370 t/s on a Ryzen-7950X!

* q8_k_r8: AVX2

I was worried that we don't have enough vector registrers on
AVX2, but it looks like it handles it just fine. We get
PP-512(LLaMA-3.1-8B) = 354 t/s on a Ryzen-5975WX.
Slightly slower than the Zen4 version with double the threads,
but still a huge upgrade compared to Q8_0_R4.

* q8_k_r4: NEON

We get PP-512(LLaMA-3.1-8B) = 159.2 t/s.
Compare this to the 128 t/s we have fr Q8_0_R4.

* q8_k_r4: go to signed ints

Why?
* On AVX2 _mm256_maddubs_epi16() may overflow, so we need to
  stay within the signed int range and use _mm256_sign_epi8.
  Not yet tested on the AVX2 comp, vut expect major slowdown.
* It is almost 10% faster on ARM_NEON. Somehow the veorrq_u8()
  needed tto convert from unsigned to signed seems to be extremely
  slow on the M2-Max
* We only lose ~0.5% in oerformance on Zen4 (there the exclusive
  or that we now use to convert fro signed to unsigned seems to be
  much faster than on M2-Max)

* Shutup useless compiler warnings

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>

1 files changed, 1 insertions, 0 deletions

diff --git a/include/llama.h b/include/llama.h
index 117f1659..e4d6ed3d 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -193,6 +193,7 @@ extern "C" {
         LLAMA_FTYPE_MOSTLY_Q6_0_R4       = 335, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_IQ2_BN_R4     = 337, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_IQ4_K_R4      = 340, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_Q8_K_R8       = 399, // except 1d tensors
 
         LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
     };