int *d_ptr; 当我要在Device(也就是GPU)上创建一个d_ptr指向的数组,并把h_ptr数组的值拷贝过去时: cudaMalloc((void**)&d_ptr, (num) * sizeof(int)); //注意这里是void** cudaMemcpy(d_ptr, h_ptr, sizeof(int) * (num), cudaMemcpyHostToDevice); 需要先在GPU上malloc一段内存,然后使用cu...
cudaError_t cudaMemcpy ( void* dst, const void* src, size_t count, cudaMemcpyKind kind ); cudaMemcpyKind有四种,并且从名字就能看出它们的作用: cudaMemcpyHostToHost:从host拷贝到host cudaMemcpyHostToDevice:从host拷贝到device cudaMemcpyDeviceToHost:从device拷贝到host cudaMemcpyDeviceToDevice:从device...
cudaError_t cudaMemcpy ( void* dst, const void* src, size_t count, cudaMemcpyKind kind )。 这个函数会拷贝数据,从dst拷贝到src,长度为count字节。至于最后一个 参数cudaMemcpyKind 是一个枚举值,可选的有: (1) cudaMemcpyHostToHost (2) cudaMemcpyHostToDevice (3) cudaMemcpyDeviceToHost (4) cu...
cudaMemcpyAsync(&d_a[offset], &a[offset], streamBytes, cudaMemcpyHostToDevice, stream[i]); kernel<<<streamSize/blockSize, blockSize, 0, stream[i]>>>(d_a, offset); cudaMemcpyAsync(&a[offset], &d_a[offset], streamBytes, cudaMemcpyDeviceToHost, stream[i]); } 另一种方法是将类似的操...
cudaMemcpyDeviceToDevice=3Device->Device cudaMemcpyDefault=4Direction of the transferisinferredfromthe pointer values. Requires unifiedvirtualaddressing 该方式使用非常简单,很多情况下效率也足以满足性能需求。 (2)高维矩阵传输:cudaMemcpy2D/cudaMalloc3D ...
cudaMemcpy(d_B.elements, B.elements, size, cudaMemcpyHostToDevice); // Allocate C in device memory Matrix d_C; d_C.width = d_C.stride = C.width; d_C.height = C.height; size = C.width * C.height * sizeof(float); cudaMalloc(&d_C.elements, size); ...
It is true that the flag name “cudaMemcpyDeviceToDevice” is confusing, but it actually mean copy of data on THE SAME device (i.e. GPU) from one memory address to another. There is not currently support in CUDA for direct copy of data from one device to another (at least not in ...
cudaMemcpyToArray(cuArrayL,0,0,pHostDataL,imgWidth*imgHeight*sizeof(uchar4),cudaMemcpyDeviceToDevice);cudaMemcpyToArray(cuArrayR,0,0,pHostDataR,imgWidth*imgHeight*sizeof(uchar4),cudaMemcpyDeviceToDevice);// 处理完后即解除资源锁定,OpenGL可以利用得到的Texture对象进行纹理贴图操作了。cudaGraphics...
cudaMemcpy(d_y, y, N*sizeof(float), cudaMemcpyHostToDevice); saxpy<<<(N+255)/256, 256>>>(N, 2.0, d_x, d_y); cudaMemcpy(y, d_y, N*sizeof(float), cudaMemcpyDeviceToHost); 使用cudaMemcpy()在主机和设备之间的数据传输是synchronous(或blocking)传输。同步数据传输在之前发出的所有 CU...