dsize * sizeof(unsigned long long), cudaHostAllocDefault); cudaCheckErrors("cudaHostAlloc1 fail"); cudaHostAlloc((void **)&h_b, dsize * sizeof
cudaStatus =cudaMalloc((void**)&dev_c, size *sizeof(float));if(cudaStatus != cudaSuccess) {fprintf(stderr,"cudaMalloc failed!");gotoError; } cudaStatus =cudaMalloc((void**)&dev_a, size *sizeof(float));if(cudaStatus != cudaSuccess) {fprintf(stderr,"cudaMalloc failed!");gotoError;...
. This dataframe could be scattered without copies to DataLoader workers. Native CUDA-accelerated basic CSV-parsing could also be nice (especially if combined with mmap-based file reading?). I can see that this is implemented bytorcharrow, maybe time to move some of its core structures to ...
In myprevious articleI explained how to install CUDA on OS X. Now it's time to start coding. However, I don't want to merely show you some piece of "ready-made" code. I would also like to also explain to you the basic concepts behind parallel programming and, specifically, GPU progr...
The reason is that your hosts arrays are not actually flat, but instead are represented as arrays of pointers. I guess to fake two-dimensional arrays in C? In any case, you either need to be more careful with your cudaMemcpy()s and copy the host arrays row-by-row, or use a flat ...
I'm opening this topic because I noticed strange behavior in the output of my code, while trying to gain insight about some basic concepts in CUDA like speed vs number of blocks/threads etc... Any help would be appreciated! First of all, here are some specs of my graphic card: ...
added#defineLLBITS 64// the number of bits in a long long#defineBSIZE ((MAXSIZE + LLBITS -1)/LLBITS)// MAXSIZE when packed into bits#definenTPB MAXSIZE// define either GPU or GPUCOPY, not both -- for timing#defineGPU//#define GPUCOPY#defineLOOPCNT 1000#definecudaCheckErrors(msg...