1. template <int BLOCK_SIZE> __global__ void
2. matrixMulCUDA_3_1w2w(float* C, float* A, float* B, int wA, int wB)
3. {
4.         // Block index
5.         int bx = blockIdx.x;
6.         int by = blockIdx.y;
7.  
8.         // Thread index
9.         int tx = threadIdx.x;
10.         int ty = threadIdx.y;
11.  
12.         // Index of the first sub-matrix of A processed by the block
13.         int aBegin = wA * BLOCK_SIZE * by;
14.  
15.         // Index of the last sub-matrix of A processed by the block
16.         int aEnd = aBegin + wA - 1;
17.  
18.         // Step size used to iterate through the sub-matrices of A
19.         int aStep = 2 * BLOCK_SIZE;
20.  
21.         // Index of the first sub-matrix of B processed by the block
22.         int bBegin = BLOCK_SIZE * bx;
23.  
24.         // Step size used to iterate through the sub-matrices of B
25.         int bStep = BLOCK_SIZE * wB;
26.  
27.         // Csub is used to store the element of the block sub-matrix
28.         // that is computed by the thread
29.         float CSub[2] = { 0,0 };
30.  
31.         // Loop over all the sub-matrices of A and B
32.         // required to compute the block sub-matrix
33.         for (int a = aBegin, b = bBegin;
34.                 a <= aEnd;
35.                 a += aStep, b += bStep)
36.         {
37.  
38.                 // Declaration of the shared memory array As used to
39.                 // store the sub-matrix of A
40.                 __shared__ float As[BLOCK_SIZE][2 * BLOCK_SIZE];
41.  
42.                 // Declaration of the shared memory array Bs used to
43.                 // store the sub-matrix of B
44.                 __shared__ float Bs[BLOCK_SIZE][2 * BLOCK_SIZE];
45.  
46.                 // Load the matrices from device memory
47.                 // to shared memory; each thread loads
48.                 // 2 elements of each matrix
49.                 As[ty][tx] = A[a + wA * ty + tx];
50.                 As[ty][tx + BLOCK_SIZE] = A[a + BLOCK_SIZE + wA * ty + tx];
51.                 Bs[ty][tx] = B[b + wB * ty + tx];
52.                 Bs[ty][tx + BLOCK_SIZE] = B[b + BLOCK_SIZE * wB * ty + tx];
53.  
54.                 // Synchronize to make sure the matrices are loaded
55.                 __syncthreads();
56.  
57.                 // Multiply the two matrices together;
58.                 // each thread computes one element
59.                 // of the block sub-matrix
60.                 for (int g = 0; g < 2; g++) {
61. #pragma unroll
62.                         for (int k = 0; k < BLOCK_SIZE; ++k)
63.                         {
64.                                 CSub[g] += As[ty][k + (g * BLOCK_SIZE)] * Bs[k][tx + (g * BLOCK_SIZE)];
65.                         }
66.                 }
67.  
68.                 // Synchronize to make sure that the preceding
69.                 // computation is done before loading two new
70.                 // sub-matrices of A and B in the next iteration
71.                 __syncthreads();
72.         }
73.  
74.         // Write the block sub-matrix to device memory;
75.         // each thread writes one element
76.         int c = wB * BLOCK_SIZE * by + BLOCK_SIZE * bx;
77.         for (int g = 0; g < 2; g++) {
78.                 C[c + (BLOCK_SIZE * g) + wB * ty + tx] = CSub[g];
79.         }
80. }
81.