实验室做并行计算的服务重启后,采用cuda接口的应用程序vasp_gpu,运行时提示: CUDA Error in cuda_main.cu, line 144: unknown error No CUDA-supporting devices found! 在Nvidia开发者论坛https://devtalk.nvidia.com/找到相关主题下的回答, When you first boot up the system in console mode, the nvidia dr...
echo $PATH/data_d/old_home/home/.conda/envs/bin:/usr/local/cuda-8.0/bin:/data_d/public/miniconda2/bin:/usr/local/cuda-9.0/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/s:/usr/local/cuda-8.0/bin/local/games:/snap/bin:/usr/local/cuda-8.0/bin CUDA_VISIBLE_DEVICES=1CU...
In this article, we explored the issue of “No GPU device found” when working with Docker on Ubuntu. We discussed two solutions to enable GPU access within a Docker container: NVIDIA-Docker and device file mounting. Both methods provide access to the GPU device, allowing you to run GPU-ac...
Hi. I was previously running cuda and cublas successfully on my laptop and within the last two weeks but then something went wrong. I am running 64-bit windows 8.1 with an NVIDIA Geforce GT 640M LE GPU. Everything was previously working using Visual Studio 2010 (unsure of the GPU driver ...
- name: cuda-container image: your-cuda-image:latest resources: limits: nvidia.com/gpu: 1 ``` 在这个示例中,我们创建了一个名为cuda-app的Deployment,指定了使用1个GPU资源,并指定了使用之前构建的带有CUDA支持的Docker镜像。 ### 总结 通过以上步骤,我们可以成功解决"cuda_error_no_binary_for_gpu"错误...
device_type: "XLA_CPU" memory_limit: 17179869184 locality { } incarnation: 4748881427766356091 physical_device_desc: "device: XLA_CPU device" ] >>> exit() my virtual env is: (tf3.8) C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\extras\demo_suite>pip list ...
查看NVIDIA_CUDA 版本,这里有有个坑:!nvidia-smi方法查看版本为11.2,而 !nvcc --version 方法查看版本为11.1。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 !nvidia-smi!nvcc--version 安装11.1 版本的会报错: 代码语言:javascript 代码运行次数:0 ...
Default Utilization Gpu : 0 % Memory : 6 % Encoder : 0 % Decoder : 0 % Ecc Mode Current : N/A Pending : N/A ECC Errors Volatile Single Bit Device Memory : N/A Register File : N/A L1 Cache : N/A L2 Cache : N/A Texture Memory : N/A Total : N/A Double Bit Device Memor...
问题描述 Issue Description cuda12.2 安装paddlepaddle==2.61后,训练报“ Cannot use GPU because there is no GPU detected on your machine” 版本&环境信息 Version & Environment Information CUDA:12.2 python:3.9
ok its been working all this time i have been doing numerous training but after updating graphics driver and cuda toolkit it has stopped working and it isnt just affecting RVC its affecting all my other ai programs i have no idea whats going on i have a cuda compatible GPU i have a nv...