即需要 Pytorch 能够切换使用系统上不同版本的 cuda ,进而编译对应的 CUDAExtension),这里即记录笔者了解到的 Ubuntu 环境下 Pytorch 在编辑 cpp 和 cuda 拓展时确定所使用 cuda 版本的基本流程以及 Pytorch 使用不同版本的 cuda 进行运行的方法。
在未来的深度学习研究中,希望读者们能够注意CUDA与PyTorch版本的一致性,从而更加高效地利用GPU进行模型训练和推理。 PyTorchTerminalUserPyTorchTerminalUserCheck CUDA versionnvcc --versionCheck PyTorch versionprint(torch.__version__)Run deep learning modelIf CUDA version mismatch, raise error 35%65%CUDA Compati...
确认驱动支持cuda11.8,参考:cuda-compatibility,以及cuda toolkit docs。 2.3 主机安装cuda11.8,以及对应的cudnn8.9.7,验证是否正常 【这个实验中pytorch自带了cuda runtime,所以其实并不需要主机上单独安装】 安装cuda11.8和对应的cudnn8.9.7: 下载并安装cuda-11.8; /usr/local/cuda链接至cuda-11.8,配置~/.bashrc环...
It seems like there is only compatibility up to cuda 12.6 here:https://flashinfer.ai/whl/ Is there any plan for compatibility with Cuda 12.8 and the pytorch nightly? (I believe they are 2.8.0) Thanks for all the hard work! Hi@RodriMora, the JIT version of flashinfer should not rely ...
在这两个不同的Docker image起的容器上,编译后的PyTorch python库倒是能运行,但是一旦要使用CUDA功能的时候,就会报错:Error 804: forward compatibility was attempted on non supported HW。 python -c 'import torch; torch.randn([3,5]).cuda()' Traceback (most recent call last): File "<string>", ...
https://docs.nvidia.com/deploy/cuda-compatibility/index.html NVIDIA® CUDA® Toolkit是一款用于构建在桌面计算机、企业和数据中心到超大规模计算环境中使用NVIDIA GPU加速的计算应用程序的开发工具。 它包括CUDA编译器工具链,包括CUDA runtime(cudart)和各种CUDA库和工具。为了构建一个应用程序,开发人员只需安装CU...
Is CUDA available: False CUDA runtime version: 11.4.315 CUDA_MODULE_LOADING set to: N/A GPU models and configuration: Could not collect Nvidia driver version: Could not collect cuDNN version: Probably one of the following: /usr/lib/aarch64-linux-gnu/libcudnn.so.8.6.0 ...
This compatibility issue can be attributed to a number of factors. One of the main causes is the mismatch in the version of CUDA capability sm_86 and the supported version by the installed PyTorch version. Another possibility is the presence of driver or network-related issues, which prevent ...
NVIDIA Jetson AGX Xavier [16GB] L4T 32.5.1 [ JetPack UNKNOWN ] Ubuntu 18.04.5 LTS Kernel Version: 4.9.201-tegra CUDA 10.2.89 CUDA Architecture: 7.2 OpenCV version: 4.1.1 OpenCV Cuda: NO CUDNN: 8.0.0.180 TensorRT: 7.1.3.0 Vision Works: 1.6.0.501 VPI: ii libnvvpi1 1.0.15 ar...
1. cuda 与 nvidia driver 版本匹配问题: CUDA Compatibility :: GPU Deployment and Management Documentation 2. 清华源下载地址 Index of /anaconda/archive/ | 清华大学开源软件镜像站 | Tsinghua Open Source Mirror 3. cuda 下载地址 老版本: CUDA Toolkit Archive | NVIDIA Developer ...