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I’ve queried the CUDA device and picked the values of some specific CUDA device attributes as follows. (Note: this question is a little bit lengthy ☺.)

I need help with the use of atomicAdd() in cuda 12.5.

I wanted to write an MLP in CUDA without any dependancy’s I apologise in advance for my messy code. Please can you examine my CUDA functions to see if there is an obvious mistake which could explain why it will not solve , as it should, the simple XoR problem. We should see a decrease in error but instead it just produces a random error. I tried to make my own CUDA rng but I am using rand() instead. I have

I’ve implemented a QR factorization algorithm in CUDA tailored to my specific needs. While testing, I’ve noticed that the execution time of my custom kernel increases exponentially as the size of the matrix grows, whereas the execution time of NVIDIA’s cuSOLVER scales much more evenly.

Can someone explain in plain English redistribution terms for cudart_110.dll?

I want to change the variable M,N by the argv parameters when the code is executed.My code[tvm_test.cu] is below:

I’ve learned from the classic sample implementation of matrix multiplication in CUDA below.

I’ve learned from the classic sample implementation of matrix multiplication in CUDA below.

I am trying to copy the variable d_output->list from device to the host using cudaMemcpy but I am obtaining Segmentation fault (core dumped) Could you please let me know why?