int peer_access_available = 0; cudaDeviceCanAccessPeer(&peer_access_available, i, j); if(peer_access_available){ cudaDeviceEnablePeerAccess(j,0); printf("> GPU%d enabled direct access to GPU%d\n", i, j); } else{ printf("(%d, %d)\n", i, j); } } } } 1. 2. 3. 4. 5....
4.查看所有可用的cpu设备的数量 print("available cpu devices: {}".format(torch.cuda.os.cpu_count())) available cpu devices: 20 这里CPU设备数量指的是逻辑处理器的数量。 5.查看所有可用的gpu设备的数量 print("available gpu devices: {}".format(torch.cuda.device_count())) available gpu devices:...
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...
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device_count=torch.cuda.device_count()print(f"Number of available CUDA devices:{device_count}") 1. 2. 3. 4. 运行上面的代码,将会输出当前系统中可用的CUDA设备数量。这个信息对于在多GPU上进行模型训练是非常有用的。 查看CUDA设备内存使用情况 ...
ubuntu-drivers devices 如下图,这里推荐我们安装的是 nvidia-driver-530 - distro。 如果我们愿意安装这个版本的驱动,则输入即可安装该驱动: sudo ubuntu-drivers autoinstall 安装过程中按照提示操作,除非你知道每个提示的真实含义,否则所有的提示都选择默认就可以了,安装完成后重启系统,NVIDIA 显卡就可以正常工作了。
为了决定是使用常规pytorch张量还是使用cuda浮点张量,我使用的库称为torch.cuda.is _ 可用()。有没有简单的方法让这个函数返回false?我尝试使用以下命令更改Cuda可视设备os.environ["CUDA_VISIBLE_DEVICES"]="" 但是torch.cuda.is _ available()仍然返回True。我查看了pytorch源代码,在我的例子中是torch. ...
pythonimporttorchtorch.__version__torch.cuda.is_available()#显示为True成功x=torch.ones(5,3)x.cuda() 方法2: 另一种方式安装 方法3: 通过官方网站安装 pip3install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1-f https://download.pytorch.org/whl/torch_stable.html ...
// create streams with highest and lowest available priorities cudaStream_t st_high, st_low; cudaStreamCreateWithPriority(&st_high, cudaStreamNonBlocking, priority_high); cudaStreamCreateWithPriority(&st_low, cudaStreamNonBlocking, priority_low); ...
CUDA Developer Tools is a series of tutorial videos designed to get you started using NVIDIA Nsight™ tools for CUDA development. It explores key features for CUDA profiling, debugging, and optimizing. CUDA Compatibility Watch Video CUDA Upgrades for Jetson Devices ...