arm64: optimize q6_k_q8_k kernel with i8mm #13519
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This PR improves q6_k_q8_k gemm kernel with arm64 i8mm instruction.
Tested on neoverse-n2 with llama3 8b q6_k quantization model.
- 40% ~ 54% S_PP uplift for all batch sizes
- 16% ~ 47% S_TG uplift for batch size 4 and above
Perplexity doesn't change with this PR.
```
// tested on neoverse-n2
$ llama-batched-bench \
-m Meta-Llama-3-8B-Instruct-Q6_K.gguf \
--no-mmap -fa \
-c 8192 -b 4096 -ub 512 -npp 128 -ntg 128 \
-npl 1,2,4,8,16,32 \
-t 64
---------------------------------------------------------------------
| PP | TG | B | S_PP t/s | S_TG t/s |
| | | | original | this pr | original | this pr |
|-------|--------|------|----------|----------|----------|----------|
| 128 | 128 | 1 | 78.52 | 109.18 | 18.63 | 18.88 |
| 128 | 128 | 2 | 84.62 | 123.94 | 34.54 | 36.92 |
| 128 | 128 | 4 | 84.36 | 122.49 | 52.65 | 61.32 |
| 128 | 128 | 8 | 90.52 | 138.87 | 63.46 | 84.41 |
| 128 | 128 | 16 | 90.11 | 138.56 | 71.04 | 101.33 |
| 128 | 128 | 32 | 89.81 | 137.79 | 75.14 | 110.47 |
---------------------------------------------------------------------
```
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I run local CI and verified this PR. There's a failure from master branch about q4_0 quantization, not related to this PR. |
slaren
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May 14, 2025
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I see ~30% end to end improvement on M3 Max, and ~60% on Snapdragon XE, with pp128 on a Q6K model. test-backend-ops vs Metal passes. Good job!
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This PR improves q6_k_q8_k gemm kernel with arm64 i8mm instruction.
Tested on neoverse-n2 with llama3 8b q6_k quantization model.
Perplexity doesn't change with this PR.
Make sure to read the contributing guidelines before submitting a PR