我目前正在学习CUDA以实现高性能计算。我有一个实现Jacobi迭代的项目。我的程序中有一个内存错误,我很难跟踪它。
我的Jacobi核心正确地运行了一次迭代,现在我正在计算旧矩阵和新矩阵之间的最大差异。如果我注释掉下一行代码:
//diff[idx] = BJacobi[idx] - AJacobi[idx];
它有效。然而,包括这行代码会导致BJacbi的数据被AJacobi的部分数据覆盖(或者至少我认为它是AJacobi的数据,它几乎是相同的模式)。这似乎是一个分配问题,但我不知道它在哪里。
__global__
void jacobi(float *diff, float *AJacobi, float *BJacobi, int *bitMask, int size)
{
int idx = blockIdx.x * blockDim.x + threadIdx.x;
float sum = 0.0;
int count = 0;
if(idx < size * size)
{
if(bitMask[idx] == 0)
{
//if left side of matrix
if(idx - 1 > 0 && idx % size != 0) {
sum += AJacobi[ idx - 1 ];
count++;
}
//if right side of matrix
if(idx + 1 < size * size && (idx + 1) % size != 0)
{
sum += AJacobi[ idx + 1 ];
count++;
}
//if top of matrix
if(idx - size > 0)
{
sum += AJacobi[ idx - size ];
count++;
}
//if bottom of matrix
if(idx + size < size * size)
{
sum += AJacobi[ idx + size ];
count++;
}
BJacobi[idx] = sum / count;
}
else BJacobi[idx] = AJacobi[idx];
}
//diff[idx] = BJacobi[idx] - AJacobi[idx];
}
在我的主要功能
readSparceMatrix(argv[1], &matrix);
array_size = matrix.rowSize * matrix.rowSize;
//we want as many or more threads then data.
dimGrid = array_size / THREADS + 1;
dimBlock = THREADS;
// ---------------------- START ALLOCATION OF DEVICE MEMEORY
err = cudaMalloc( (void**)&diff, array_size * sizeof(float));
if (err != cudaSuccess) {
fprintf (stderr, "cudaMalloc: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMalloc( (void**)&AJacobi, array_size * sizeof(float) );
if (err != cudaSuccess) {
fprintf (stderr, "cudaMalloc: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMalloc( (void**)&BJacobi, array_size * sizeof(float) );
if (err != cudaSuccess) {
fprintf (stderr, "cudaMalloc: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMalloc( (void**)&MaxDiffTree, array_size * sizeof(float) );
if (err != cudaSuccess) {
fprintf (stderr, "cudaMalloc: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMalloc( (void**)&bitMask, array_size * sizeof(int) );
if (err != cudaSuccess) {
fprintf (stderr, "cudaMalloc: %s\n", cudaGetErrorString(err));
exit(1);
}
// ---------------------- START INTITILIZATION OF DEVICE MEMERY
err = cudaMemset(diff, 1.0, array_size * sizeof(float));
if (err != cudaSuccess) {
fprintf (stderr, "cudaMemcpy: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMemset(BJacobi, 0.0, array_size * sizeof(float));
if (err != cudaSuccess) {
fprintf (stderr, "cudaMemcpy: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMemset(MaxDiffTree, 0.0, array_size * sizeof(float));
if (err != cudaSuccess) {
fprintf (stderr, "cudaMemcpy: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMemcpy(AJacobi, matrix.data, array_size * sizeof(float) ,cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf (stderr, "cudaMemcpy: %s\n", cudaGetErrorString(err));
exit(1);
}
err = cudaMemcpy(bitMask, matrix.mask, array_size * sizeof(int) ,cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
fprintf (stderr, "cudaMemcpy: %s\n", cudaGetErrorString(err));
exit(1);
}
// ---------------------- START MAIN JACOBI LOOP
//while(MaxDiff > delta){
jacobi<<<dimGrid, dimBlock>>>(diff, AJacobi, BJacobi, bitMask, matrix.rowSize);
答案 0 :(得分:1)
所以这实际上是一个简单的错误,我花了很长时间试图找出答案。问题发生是因为我有更多线程然后数据。因此,我的线程索引超出了我的数组范围。我的代码中的第一个if语句是为了检查它,但是我的差异分配是在我的索引检查之外。在if检查下移动diff语句解决了我的问题。
if(idx < size * size){
if(bitMask[idx] == 0){
//if left side of matrix
if(idx - 1 > 0 && idx % size != 0) {
sum += src[ idx - 1 ];
count++;
}
//if right side of matrix
if(idx + 1 < size * size && (idx + 1) % size != 0)
{
sum += src[ idx + 1 ];
count++;
}
//if top of matrix
if(idx - size > 0)
{
sum += src[ idx - size ];
count++;
}
//if bottom of matrix
if(idx + size < size * size)
{
sum += src[ idx + size ];
count++;
}
dst[idx] = sum / count;
}
else dst[idx] = src[idx];
diff[idx] = dst[idx] - src[idx];
}