Q8_KV: 8-bit quantization type targeting the KV cache (#208)

* Adding q8_KV - Basics + AVX2 gemm/gemv

* q8_KV: Better AVX2 gemm

* q8_KV: Better Zen4 gemm

We get 225.7 t/s for L3-8B. In comparison q8_0 without
run-tinme-repacking is at 169 t/s.

* q8_KV: AVX2 gemm/gemv

We get 254 t/s for L3-8B vs 194 t/s for q8_0 without rtr.

* q8_KV: be able to use it for K cache

This required quite a few fixes in ggml and llama.cpp:
* ggml: do not calculate row size as n/block_size*type_size. I had
  removed most of it when implementing the quants with per row scale,
  bit it was stull lurking in ggml_copy. Not sure if these were the last
  remnants of ggmil-style row sizes, or if there are still places left
* llama.cpp: get rid of the the 1d K cache assumption. Create and manage
  the K-cache as a 2D tensor so we can have per row meta data as needed
  by q8_KV.

Using q8_KV for K-cache results in non-negligible performance gains.
More details to follow, but for DeepSeek-Lite with MLA, we get
18% speedup for PP-8192 compared to q8_0 K-cache.

* q8_KV: be able to use it for K cache in FA

* q8_KV: repack it for K*Q in FA

* q8_KV: slightly faster gemv on Zen4

* q8_KV: slightly faster gemv on Zen4

* q8_KV: ARM_NEON

We get PP-512 = 167 t/s for L3-8B without interleaving!
We do the interleaving on the fly, so I wonder if this
could be done for other quants as well.

* q8_KV: use it in FA on NEON

* q8_KV_r8 - repacked q8_KV

On Zen4 it is slower than q8_k_r8 (292 vs 370 t/s)
This makes no sense whatsoever as the q8_KV_r8 GEMM is
basically the q8_k_r8 GEMM with the unnecessary block stuff
removed (so, one would think that it would be faster).

* q8_KV_r8: don't use nrc_y = 16 on Zen4

This is faster - 350 t/s. Why?
Much better than the 290 t/s we had before, but still slower
than the 370 t/s for q8_k_r8.

* q8_KV: nrc_y = 16 also doesn't pay off in FA

* Minor

---------

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

1 files changed, 4 insertions, 0 deletions

diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h
index 66bcb25a..d2131a15 100644
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@@ -416,6 +416,7 @@ extern "C" {
         GGML_TYPE_Q8_K32  = 148,
         GGML_TYPE_Q8_KR8  = 149,
         GGML_TYPE_Q8_K128 = 150,
+        GGML_TYPE_Q8_KV   = 151,
 
         GGML_TYPE_Q4_0_R8   = 202,
         GGML_TYPE_Q5_0_R4   = 206,
@@ -442,6 +443,7 @@ extern "C" {
         GGML_TYPE_IQ4_K_R4  = 339,
         GGML_TYPE_IQ5_K_R4  = 340,
         GGML_TYPE_IQ4_KS_R4 = 344,
+        GGML_TYPE_Q8_KV_R8  = 398,
         GGML_TYPE_Q8_K_R8   = 399,
         GGML_TYPE_COUNT,
     };
@@ -501,6 +503,7 @@ extern "C" {
         GGML_FTYPE_MOSTLY_IQ4_KS  = 137, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ2_KS  = 138, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ4_KSS = 139, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q8_KV   = 140, // except 1d tensors
                                          //
         GGML_FTYPE_MOSTLY_Q4_0_R8   = 202, // except 1d tensors
         GGML_FTYPE_MOSTLY_Q8_0_R8   = 207, // except 1d tensors
@@ -527,6 +530,7 @@ extern "C" {
         GGML_FTYPE_MOSTLY_IQ4_K_R4  = 332, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ5_K_R4  = 333, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ4_KS_R4 = 337, // except 1d tensors
+        GGML_FTYPE_MOSTLY_Q8_KV_R8  = 398, // except 1d tensors
         GGML_FTYPE_MOSTLY_Q8_K_R8   = 399, // except 1d tensors
     };