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quant_cuda_kernel.cu
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quant_cuda_kernel.cu
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#include <torch/all.h>
#include <torch/python.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_fp16.h>
template <typename scalar_t>
__global__ void VecQuant3MatMulKernel(
const scalar_t* __restrict__ vec,
const int* __restrict__ mat,
scalar_t* __restrict__ mul,
const scalar_t* __restrict__ scales,
const scalar_t* __restrict__ zeros,
int height,
int width
);
__global__ void VecQuant3MatMulKernelFaster(
const half2* __restrict__ vec,
const int* __restrict__ mat,
float* __restrict__ mul,
const float* __restrict__ scales,
const float* __restrict__ zeros,
int height,
int width
);
const int BLOCKWIDTH = 256;
const int BLOCKHEIGHT = 24;
void vecquant3matmul_cuda(
torch::Tensor vec,
torch::Tensor mat,
torch::Tensor mul,
torch::Tensor scales,
torch::Tensor zeros
) {
int height = mat.size(0);
int width = mat.size(1);
dim3 blocks(
(height + BLOCKHEIGHT - 1) / BLOCKHEIGHT,
(width + BLOCKWIDTH - 1) / BLOCKWIDTH
);
dim3 threads(BLOCKWIDTH);
AT_DISPATCH_FLOATING_TYPES(
vec.type(), "vecquant3matmul_cuda", ([&] {
VecQuant3MatMulKernel<<<blocks, threads>>>(
vec.data<scalar_t>(), mat.data<int>(), mul.data<scalar_t>(),
scales.data<scalar_t>(), zeros.data<scalar_t>(),
height, width
);
})
);
}
void vecquant3matmul_faster_cuda(
torch::Tensor vec,
torch::Tensor mat,
torch::Tensor mul,
torch::Tensor scales,
torch::Tensor zeros
) {
int height = mat.size(0);
int width = mat.size(1);
dim3 blocks(
(height + BLOCKHEIGHT - 1) / BLOCKHEIGHT,
(width + BLOCKWIDTH - 1) / BLOCKWIDTH
);
dim3 threads(BLOCKWIDTH);
VecQuant3MatMulKernelFaster<<<blocks, threads>>>(
(half2*) vec.data_ptr(),
mat.data_ptr<int>(),
mul.data_ptr<float>(),
scales.data_ptr<float>(),
zeros.data_ptr<float>(),
height, width
);
}
__device__ inline unsigned int as_unsigned(int i) {
return *reinterpret_cast<unsigned int*>(&i);
}
template <typename scalar_t>
__global__ void VecQuant3MatMulKernel(
const scalar_t* __restrict__ vec,
const int* __restrict__ mat,
scalar_t* __restrict__ mul,
const scalar_t* __restrict__ scales,
const scalar_t* __restrict__ zeros,
int height,
int width
) {
int row = BLOCKHEIGHT * blockIdx.x;
int col = BLOCKWIDTH * blockIdx.y + threadIdx.x;
__shared__ scalar_t blockvec[BLOCKWIDTH];
blockvec[threadIdx.x] = vec[(row / BLOCKHEIGHT) * BLOCKWIDTH + threadIdx.x];
__syncthreads();
scalar_t scale = scales[col];
scalar_t zero = zeros[col];
scalar_t res = 0;
int i = width * row + col;
int k = 0;
unsigned int tmp1;
unsigned int tmp2;
unsigned int tmp;
while (k < BLOCKWIDTH) {
tmp1 = as_unsigned(mat[i]);
res += (scale * scalar_t((tmp1 >> 0) & 0x7) - zero) * blockvec[k + 0];
res += (scale * scalar_t((tmp1 >> 3) & 0x7) - zero) * blockvec[k + 1];
res += (scale * scalar_t((tmp1 >> 6) & 0x7) - zero) * blockvec[k + 2];
res += (scale * scalar_t((tmp1 >> 9) & 0x7) - zero) * blockvec[k + 3];
res += (scale * scalar_t((tmp1 >> 12) & 0x7) - zero) * blockvec[k + 4];
res += (scale * scalar_t((tmp1 >> 15) & 0x7) - zero) * blockvec[k + 5];
res += (scale * scalar_t((tmp1 >> 18) & 0x7) - zero) * blockvec[k + 6];
res += (scale * scalar_t((tmp1 >> 21) & 0x7) - zero) * blockvec[k + 7];
res += (scale * scalar_t((tmp1 >> 24) & 0x7) - zero) * blockvec[k + 8];
res += (scale * scalar_t((tmp1 >> 27) & 0x7) - zero) * blockvec[k + 9];
i += width;
tmp2 = as_unsigned(mat[i]);
tmp = (tmp1 >> 30) | ((tmp2 << 2) & 0x4);
tmp2 >>= 1;
res += (scale * scalar_t(tmp) - zero) * blockvec[k + 10];
k += 11;
res += (scale * scalar_t((tmp2 >> 0) & 0x7) - zero) * blockvec[k + 0];
res += (scale * scalar_t((tmp2 >> 3) & 0x7) - zero) * blockvec[k + 1];
res += (scale * scalar_t((tmp2 >> 6) & 0x7) - zero) * blockvec[k + 2];
res += (scale * scalar_t((tmp2 >> 9) & 0x7) - zero) * blockvec[k + 3];
res += (scale * scalar_t((tmp2 >> 12) & 0x7) - zero) * blockvec[k + 4];
res += (scale * scalar_t((tmp2 >> 15) & 0x7) - zero) * blockvec[k + 5];
res += (scale * scalar_t((tmp2 >> 18) & 0x7) - zero) * blockvec[k + 6];
res += (scale * scalar_t((tmp2 >> 21) & 0x7) - zero) * blockvec[k + 7];
res += (scale * scalar_t((tmp2 >> 24) & 0x7) - zero) * blockvec[k + 8];
res += (scale * scalar_t((tmp2 >> 27) & 0x7) - zero) * blockvec[k + 9];
i += width;
tmp1 = as_unsigned(mat[i]);
tmp = (tmp2 >> 30) | ((tmp1 << 1) & 0x6);
tmp1 >>= 2;
res += (scale * scalar_t(tmp) - zero) * blockvec[k + 10];
k += 11;
res += (scale * scalar_t((tmp1 >> 0) & 0x7) - zero) * blockvec[k + 0];
res += (scale * scalar_t((tmp1 >> 3) & 0x7) - zero) * blockvec[k + 1];
res += (scale * scalar_t((tmp1 >> 6) & 0x7) - zero) * blockvec[k + 2];
res += (scale * scalar_t((tmp1 >> 9) & 0x7) - zero) * blockvec[k + 3];
res += (scale * scalar_t((tmp1 >> 12) & 0x7) - zero) * blockvec[k + 4];
res += (scale * scalar_t((tmp1 >> 15) & 0x7) - zero) * blockvec[k + 5];
res += (scale * scalar_t((tmp1 >> 18) & 0x7) - zero) * blockvec[k + 6];
res += (scale * scalar_t((tmp1 >> 21) & 0x7) - zero) * blockvec[k + 7];
res += (scale * scalar_t((tmp1 >> 24) & 0x7) - zero) * blockvec[k + 8];
res += (scale * scalar_t((tmp1 >> 27) & 0x7) - zero) * blockvec[k + 9];
i += width;
k += 10;
}
atomicAdd(&mul[col], res);
}
__global__ void VecQuant3MatMulKernelFaster(
const half2* __restrict__ vec,
const int* __restrict__ mat,
float* __restrict__ mul,
const float* __restrict__ scales,
const float* __restrict__ zeros,
int height,
int width
) {
const int blockwidth2 = BLOCKWIDTH / 2;
int row = BLOCKHEIGHT * blockIdx.x;
int col = BLOCKWIDTH * blockIdx.y + threadIdx.x;
__shared__ half2 blockvec[blockwidth2];
if (threadIdx.x < blockwidth2)
blockvec[threadIdx.x] = vec[(row / BLOCKHEIGHT) * blockwidth2 + threadIdx.x];
__shared__ half2 deq2[64][32];
int val = threadIdx.x / 32;
int off = threadIdx.x % 32;
for (; val < 64; val += BLOCKWIDTH / 32) {
deq2[val][off] = __halves2half2(
__int2half_rn(val & 0x7), __int2half_rn(val >> 3)
);
}
half2 scale = __float2half2_rn(scales[col]);
half2 zero = __float2half2_rn(-zeros[col]);
int i = width * row + col;
int k = 0;
float res = 0;
half2 res2;
unsigned int tmp1;
unsigned int tmp2;
unsigned int tmp;
__syncthreads();
while (k < blockwidth2) {
res2 = {};
tmp1 = as_unsigned(mat[i]);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 0) & 0x3f][off], scale, zero), blockvec[k + 0], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 6) & 0x3f][off], scale, zero), blockvec[k + 1], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 12) & 0x3f][off], scale, zero), blockvec[k + 2], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 18) & 0x3f][off], scale, zero), blockvec[k + 3], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 24) & 0x3f][off], scale, zero), blockvec[k + 4], res2);
i += width;
tmp2 = as_unsigned(mat[i]);
tmp = (tmp1 >> 30) | ((tmp2 << 2) & 0x3c);
res2 = __hfma2(__hfma2(deq2[tmp][off], scale, zero), blockvec[k + 5], res2);
tmp2 >>= 4;
k += 6;
res2 = __hfma2(__hfma2(deq2[(tmp2 >> 0) & 0x3f][off], scale, zero), blockvec[k + 0], res2);
res2 = __hfma2(__hfma2(deq2[(tmp2 >> 6) & 0x3f][off], scale, zero), blockvec[k + 1], res2);
res2 = __hfma2(__hfma2(deq2[(tmp2 >> 12) & 0x3f][off], scale, zero), blockvec[k + 2], res2);
res2 = __hfma2(__hfma2(deq2[(tmp2 >> 18) & 0x3f][off], scale, zero), blockvec[k + 3], res2);
i += width;
tmp1 = as_unsigned(mat[i]);
tmp = (tmp2 >> 24) | ((tmp1 << 4) & 0x30);
res2 = __hfma2(__hfma2(deq2[tmp][off], scale, zero), blockvec[k + 4], res2);
tmp1 >>= 2;
k += 5;
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 0) & 0x3f][off], scale, zero), blockvec[k + 0], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 6) & 0x3f][off], scale, zero), blockvec[k + 1], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 12) & 0x3f][off], scale, zero), blockvec[k + 2], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 18) & 0x3f][off], scale, zero), blockvec[k + 3], res2);
res2 = __hfma2(__hfma2(deq2[(tmp1 >> 24) & 0x3f][off], scale, zero), blockvec[k + 4], res2);
i += width;
k += 5;
res += __half2float(res2.x) + __half2float(res2.y);
}
atomicAdd(&mul[col], res);
}