I am using nvfortran 23.11 and Cuda 12.3 - just updated both. Previously, I was able to use cudaGetDeviceProperties as in: istat = cudaGetDeviceProperties(prop, 0) if(istat /= cudaSuccess) then write(,) ‘GetDevice kernel error:’, cudaGetErrorString(istat) ...
当你在使用PaddlePaddle的GPU版本时遇到“your cuda device is not set properly”的错误,这通常意味着CUDA环境没有被正确配置或识别。以下是一些步骤和代码片段,帮助你检查和解决这个问题: 1. 检查PaddlePaddle是否为GPU版本 首先,确保你安装的是PaddlePaddle的GPU版本。你可以通过运行以下Python代码来检查: python import...
I am using nvfortran 23.11 and Cuda 12.3 - just updated both. Previously, I was able to use cudaGetDeviceProperties as in: istat = cudaGetDeviceProperties(prop, 0) if(istat /= cudaSuccess) then write(,) ‘GetDevice k…
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Why must bind_to_thread be called before using CudaDevice on a separate thread? #271 workingjubilee opened this issue Jul 10, 2024· 0 comments Comments Copy link workingjubilee commented Jul 10, 2024 It is a safe function. Are there other safe functions which are depending on this ...
The text was updated successfully, but these errors were encountered: zhangQiWorrchanged the titleK8S: Using CUDA MPS to enable GPU sharing, error:error checking MPS daemon healthApr 11, 2024 github-actionsbotadded thelifecycle/staleDenotes an issue or PR has remained open with no activity and...
The algorithm is implemented on a graphics processing unit (GPU) using the compute unified device architecture (CUDA) development environment. The result shows better performance compared to the one implemented on a CPU.关键词: coprocessors inspection liquid crystal displays parallel algorithms thin ...
# [-0.0000, -0.0000, 0.2452, ..., 0.1763, -0.0000, -0.2748]], device='cuda:0'), # batch_sizes=tensor([ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])) ...
Using NVC++ 23.9, the code successfully builds withnvc++ -cuda, but we get device linker errors for device-side cuRAND symbols: [ 66%] Linking CUDA executable 3d/Test_Amr_Advection_AmrCore_3d nvlink error : Multiple definition of 'precalc_xorwow_matrix' in 'CMakeFiles/Test_Amr_Advec...
cudaDeviceProp prop;//cuda设备属性对象if(cudaGetDeviceProperties(∝, i) == cudaSuccess) { std::cout<<"设备名称:"<<prop.name<<"\n"; std::cout<<"计算能力的主代号:"<<prop.major<<"\t"<<"计算能力的次代号:"<<prop.minor<<"\n"; ...