Fixed bug in Q2_K CUDA dot product kernel
Stranegly enough, for the few prompts I tried with the 7B model the responses looked perfectly reasonable. Only realized something is not quite right when I tried the larger models and started getting nonse back. In any case, Q2_K single token evaluation time on an RTX 4080 in a Ryzen7950X box iusing CUDA and model fully loaded on the GPU are ~15.5 ms for 7B, ~25.4 ms for 13B, and ~55.8 ms for 30B. The max number of layers that fit in VRAM for The 65B is 32. With that, we get ~330 ms per token, which is not that much faster than just running on the CPU (~470 ms per token).
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1 changed files with 4 additions and 3 deletions
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@ -278,7 +278,7 @@ static __device__ void vec_dot_q2_K(const void * vx, const int ib, const int iqs
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+ y[ 64] * (dall * ((s[4] & 0xF) * ((q[ 0] >> 4) & 3)) - dmin * (s[4] >> 4))
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+ y[ 96] * (dall * ((s[6] & 0xF) * ((q[ 0] >> 6) & 3)) - dmin * (s[6] >> 4))
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+ y[ 16] * (dall * ((s[1] & 0xF) * ((q[16] >> 0) & 3)) - dmin * (s[1] >> 4))
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+ y[ 48] * (dall * ((s[3] & 0xF) * ((q[16] >> 2) & 3)) - dmin * (s[1] >> 4))
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+ y[ 48] * (dall * ((s[3] & 0xF) * ((q[16] >> 2) & 3)) - dmin * (s[3] >> 4))
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+ y[ 80] * (dall * ((s[5] & 0xF) * ((q[16] >> 4) & 3)) - dmin * (s[5] >> 4))
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+ y[112] * (dall * ((s[7] & 0xF) * ((q[16] >> 6) & 3)) - dmin * (s[7] >> 4));
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@ -753,8 +753,9 @@ static void dequantize_mul_mat_vec_q8_0_cuda(const void * vx, const float * y, f
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static void dequantize_mul_mat_vec_q2_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % QK_K == 0);
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const dim3 block_dims(32, 2, 1);
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dequantize_mul_mat_vec_k<32, vec_dot_q2_K><<<nrows/2, block_dims, 0, stream>>>(vx, y, dst, ncols);
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const int ny = 2;
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const dim3 block_dims(32, ny, 1);
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dequantize_mul_mat_vec_k<32, vec_dot_q2_K><<<(nrows + ny - 1)/ny, block_dims, 0, stream>>>(vx, y, dst, ncols);
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}
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static void dequantize_mul_mat_vec_q3_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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