CUDA: quantized GEMM for for IQ2_KS, IQ2_K, IQ3_K#418
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Wow the IQ2_KS improved around 35%!? The 32 block I'd probably try out the larger IQ3_KS and especially IQ5_KS for some mixes in the future if you decide to add them. |
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This PR is a follow up of #417 and (almost) completes the quantized matrix multiplication (a.k.a. MMQ) implementation for
IQX_Kquants. The only one missing isIQ4_KSS, but I don't think I'll do that one as the packing is much too complicated.There are larger performance gains for
IQ2_KS(~35%) than forIQ2_KandIQ3_K(~10%). This is due toIQ2_KShaving blocks of 32 and thus being able to use the more efficient GEMM kernel (see discussion in #417).The graph illustrates the performance improvements for the same setup as in #417.
Looking at this graph and in the graph in #417, I almost feel like adding
IQ3_KSandIQ5_KSas 3- and 5-bit quants with blocks of 32.