53 lines
1.5 KiB
Plaintext
53 lines
1.5 KiB
Plaintext
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#ifndef MULTIPLICATION_CUH
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#define MULTIPLICATION_CUH
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#include "matrix.cuh"
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#include "gf28.cuh"
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// 处理32base列的所有行
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__global__ void gpu_addmul_kernel(base_t *a, size_t a_pitch, base_t *b, size_t b_pitch, base_t *c, size_t c_pitch, size_t nrows, size_t width)
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{
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__shared__ __align__(8) base_t src[base_deg][THREAD_X];
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size_t r = threadIdx.y;
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size_t w = blockIdx.x * blockDim.x + threadIdx.x;
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if (w >= width)
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{
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return;
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}
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if (r < nrows && w < width)
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src[threadIdx.y][threadIdx.x] = *at_pitch(b, b_pitch, r, w);
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else
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src[threadIdx.y][threadIdx.x] = base_zero;
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__syncthreads();
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for (; r < nrows; r += base_deg)
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{
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base_t val = *at_pitch(a, a_pitch, r, 0);
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base_t temp = base_zero;
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for (size_t i = 0; i < base_deg; i++)
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{
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temp ^= mul_base(get8(val, i), src[i][threadIdx.x]);
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}
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*at_pitch(c, c_pitch, r, w) ^= temp;
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}
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}
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__host__ void GF28Matrix::gpu_addmul(const GF28Matrix &a, const GF28Matrix &b, const GF28 &gf)
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{
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assert(a.ncols == b.nrows && a.nrows == nrows && b.ncols == ncols);
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cudaMemcpyToSymbol(d_mul_table, gf.mul_table, (1 << base_deg) * (1 << base_deg) * sizeof(gf28_t));
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for (size_t w = 0; w < a.width; w++)
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{
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dim3 block(THREAD_X, THREAD_Y);
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dim3 grid((b.width - 1) / block.x + 1);
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cudaDeviceSynchronize();
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gpu_addmul_kernel<<<grid, block>>>(a.at_base(0, w), a.pitch, b.at_base(w * base_num, 0), b.pitch, data, pitch, nrows, width);
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}
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cudaDeviceSynchronize();
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}
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#endif
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