这是因为显卡驱动在更新过程中对CUDA是backward Compatibility(向后兼容)的，直观来说就是510.47.03版的...
在查阅英伟达官网[CUDA兼容性](CUDA Compatibility)后，发现470.57.02的驱动支持向后兼容，也就是说经过...
安装edgeai-torchvision环境的过程中,一直出错,后来深入理解源码,发现主要原因是源码编译安装torchvision时,是从CUDA_HOME/NVCC中获取CUDA版本,故虚拟环境的CUDA版本需要和系统的CUDA版本一致,而目前系统版本是CUDA11.7,虚拟环境安装pytorch使用的是cuda11.3,故需要重新安装系统版本CUDA11.3; edgeai-torchvision/torchvision/ext...
On the other hand, when running on a newer device than what is natively supported, the library is inforward-compatibilitymode, whereby PTX JIT compilation of CUDA kernels will be used to support library workloads. Note Each version of the cuDNN library stores the highest SM number of the GPU...
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After reading #915 (go do that now!), you may be wondering about Thrust's compatibility with older versions of CUDA. Historically, most of Thrust's CUDA backend has worked with older versions of CUDA, with some features requiring a parti...
Can the NVIDIA RTX A5500 laptop graphics card be used to work with PyTorch? I checked the official NVIDIA documentation and I found that the last CUDA-Enabled NVIDIA RTX Mobile GPU is RTX A5000 - therefore, I wonder if …
since it does not appear in this link CUDA GPUs - Compute Capability | NVIDIA Developer, can I use the drivers of the portable version of the same graphics card to be able to work with it? How can I do it so that it can work with this limitation?
For more information, see CUDA Compatibility. Minor version compatibility continues into CUDA 12.x. However, as 12.0 is a new major release, the compatibility guarantees are reset. Applications that used minor version compatibility in 11.x may have issues when linking against 12.0. Either re...
Moreover, features such as forward compatibility and minor version compatibility help you pick up combinations of driver and toolkit, and tailor it per your application needs. CUDA upgradable package on Jetson Starting from CUDA 11.8, CUDA has introduced an upgrade path that provides Jetson ...