CUDA是否可用:通过torch.cuda.is_available()方法来判断系统是否安装了CUDA。 当前设备数量:使用torch.cuda.device_count()来获取可用的CUDA设备数量。 当前设备的名称:通过torch.cuda.get_device_name(device)来获取指定设备的名称。 当前设备的内存使用情况:可以利用torch.cuda.memory_allocated()和torch.cuda.memory_...
擅长全栈开发、运维和人工智能技术。...引言在深度学习模型的训练过程中,内存不足问题(即CUDA Out of Memory错误)常常会困扰开发者。...这个错误通常是由于显存(GPU内存)不够用导致的,尤其是在训练大规模模型或处理高分辨率图像时更加明显。
CUDA-MEMCHECK DU-05355-001_v11.6 | 1 Introduction 1.4. CUDA-MEMCHECK tools Tools allow use the basic CUDA-MEMCHECK infrastructure to provide different checking mechanisms. Currently, the supported tools are : ‣ Memcheck - The memory access error and leak detection ...
cuda-gdb-10-1 cuda-gpu-library-advisor-10-1 cuda-libraries-10-1 cuda-libraries-dev-10-1 cuda-license-10-1 cuda-memcheck-10-1 cuda-misc-headers-10-1 cuda-npp-10-1 cuda-npp-dev-10-1 cuda-nsight-10-1 cuda-nsight-compute-10-1 cuda-nsight-systems-10-1 cuda-nvcc-10-1 cuda-nvdisa...
问警告(theano.sandbox.cuda)：CUDA已安装，但设备gpu不可用(错误: cuda不可用)EN对于刚接触人工智能领域不久的我而言，装 CUDA 等一些跑模型需要用到的工具是一件痛苦的事，稍不注意就会导致版本依赖问题，最终可能会需要你把前面安装的东西都卸载掉并重新下载，故本文记录如何卸载 CUDA 使得卸载干净。
// pine memory malloc CHECK(cudaMallocHost((float**)&a_d,nByte)); 零拷贝内存 (mapped memory) 一般的内存指针(cudaMalloc/cudaMallocHost):主机不能直接访问设备内存,设备不能直接访问主机内存。 mapped memory 的优势: 当设备内存不足的时候可以利用主机内存 避免主机和设备之间的显式内存传输 提高PCIe传...
[idx];}// ...// check for p2p accessintp2p_1to2;cudaDeviceCanAccessPeer(&p2p_1to2,gpu1,gpu2);// 0 代表不支持intp2p_2to1;cudaDeviceCanAccessPeer(&p2p_2to1,gpu2,gpu1);if(p2p_1to2==0||p2p_2to1==0)return1;cudaSetDevice(gpu1);cudaDeviceEnablePeerAccess(gpu2,0);...
1.1. About CUDA-MEMCHECK CUDA-MEMCHECK is a functional correctness checking suite included in the CUDA toolkit. This suite contains multiple tools that can perform different types of checks. The memcheck tool is capable of precisely detecting and attributing out of bounds and misaligned memory acce...
name: Checkout private repo uses: actions/checkout@v2 with: repository: getsentry/my-private-repo token: ${{ steps.my-app.outputs.token }} cosmosmosco commented Apr 24, 2023 Have you solved this problem yet ? widedh commented Apr 25, 2023 Hello, I have the same issue. Did you find...
@dcruiz01@SunixLiu@AlpinDalevLLM is designed to take almost all of your GPU memory. Could you double-check your GPU is not used by other processes when using vLLM? Thanks, I think I understand now. Asomewhat @AlpinDaleGood question. You can use thetensor_parallel_sizeargument for multi...