* Experiments for 2.6875 bpw quants
At least according to rmse, this is significantly better than
q2_K, while using only 1/16 more bits per weight.
* iq2_kl: basics
* iq2_kl: CUDA dequantize
* iq2_kl: small improvement in PPL
Also check the two neighbouring values for the block scale
and use the one that minimizes RMSE.
* iq2_kl: MMQ
Quite good: PP-512(L3-8B) = 8472 t/s.
* iq2_kl: MMVQ
We get PP-128(L3-8B) = 162 t/s.
Which means that this is not quite as good as it should be as
(almost) same bpq q2_K is at 170 t/s.
* iq2_kl: Zen4 GEMM/GEMV
Not particularly fast. I may need to think about rearranging the bits.
* iq2_kl: better Zen4
* iq2_kl: convert/repack to q8_k_r8 (AVX2)
* iq2_kl: AVX2 GEMM/GEMV
* iq2_kl: WIP NEON
The compiler started crashing!!!
* iq2_kl: NEON
Had to work around a compiler crash when using vzip2q_u8 using
vqtbl2q_u8.
* iq2_kl: convert/repack to q8_k_r8 (NEON)
* iq2_kl: Metal dequantize
* iq2_kl: Metal GEMV - pretty slow
* iq2_kl: Metal GEMV - slightly better (40 t/s -> 44.5 t/s)
* iq2_kl: Metal GEMV - slightly better (44.5 t/s -> 46.5 t/s)
* iq2_kl: Metal GEMV - slightly better (46.5 t/s -> 47.2 t/s)
* iq2_kl: slightly better Metal dequantize
PP-512 goes to 476 t/s up from 466 t/s.
* iq2_kl: slightly better Metal dequantize
PP-512 goes to 492 t/s up from 476 t/s.
* Add iq2_kl to constants.py
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Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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