[英]Matrix Multiplication CUDA
我一直在閱讀幾個網站,甚至使用NVIDA的代碼作為指南,但我仍然得到了錯誤的答案。 主要詢問用戶的大小,並顯示A和B然后顯示結果矩陣C.但是說我為A和B運行2x2矩陣這是我的樣本輸出:
Matrix A
0.000000 8.000000
2.000000 2.000000
Matrix B
3.000000 1.000000
5.000000 7.000000
Matrix C (Results)
0.000000 9.000000
7.000000 4.000000
但這是不正確的。 它應該是:
40.000 56.000
16.000 16.000
我將它從小數改為整數,以便更容易檢查,我發現它是不正確的。 我不明白為什么它會不正確,特別是即使我從他們的代碼示例中采取了它。
#ifndef _MATRIXMUL_KERNEL_H_
#define _MATRIXMUL_KERNEL_H_
#include <stdio.h>
// Thread block size
#define BLOCK_SIZE 16
#define TILE_SIZE 16
// CUDA Kernel
__global__ void matrixMul( float* C, float* A, float* B, int wA, int wB)
{
// Block index
int bx = blockIdx.x;
int by = blockIdx.y;
// Thread index
int tx = threadIdx.x;
int ty = threadIdx.y;
// Index of the first sub-matrix of A processed
// by the block
int aBegin = wA * BLOCK_SIZE * by;
// Index of the last sub-matrix of A processed
// by the block
int aEnd = aBegin + wA - 1;
// Step size used to iterate through the
// sub-matrices of A
int aStep = BLOCK_SIZE;
// Index of the first sub-matrix of B processed
// by the block
int bBegin = BLOCK_SIZE * bx;
// Step size used to iterate through the
// sub-matrices of B
int bStep = BLOCK_SIZE * wB;
float Csub=0;
// Loop over all the sub-matrices of A and B
// required to compute the block sub-matrix
for (int a = aBegin, b = bBegin; a <= aEnd; a += aStep, b += bStep)
{
// Declaration of the shared memory array As
// used to store the sub-matrix of A
__shared__ float As[BLOCK_SIZE][BLOCK_SIZE];
// Declaration of the shared memory array Bs
// used to store the sub-matrix of B
__shared__ float Bs[BLOCK_SIZE][BLOCK_SIZE];
// Load the matrices from global memory
// to shared memory; each thread loads
// one element of each matrix
As[ty][tx] = A[a + wA * ty + tx];
Bs[ty][tx] = B[b + wB * ty + tx];
// Synchronize to make sure the matrices
// are loaded
__syncthreads();
// Multiply the two matrices together;
// each thread computes one element
// of the block sub-matrix
for (int k = 0; k < BLOCK_SIZE; ++k)
Csub += As[ty][k] * Bs[k][tx];
// Synchronize to make sure that the preceding
// computation is done before loading two new
// sub-matrices of A and B in the next iteration
__syncthreads();
}
// Write the block sub-matrix to device memory;
// each thread writes one element
int c = wB * BLOCK_SIZE * by + BLOCK_SIZE * bx;
C[c + wB * ty + tx] = Csub;
}
#endif // #ifndef _MATRIXMUL_KERNEL_H_
主機代碼:
//perform the calculation
//setup execution parameters
dim3 threads(BLOCK_SIZE, BLOCK_SIZE);
dim3 grid(c.colSize / threads.x, c.rowSize / threads.y);
// execute the kernel
matrixMul<<< grid, threads >>>(deviceMatrixC, deviceMatrixA, deviceMatrixB, a.colSize, b.colSize);
謝謝你的幫助,丹
您隱式使用的代碼要求矩陣的大小是塊大小的四倍(在這種情況下為16x16)。 內積計算一次處理一個區塊寬度,而不檢查超出范圍內存訪問。 因此,2x2矩陣將無法正常工作。
如果您嘗試使用16x16輸入運行內核(例如將2x2大小寫填充為16x16的零填充),則應該能夠確認結果。
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.