我对运行which nvcc和显示的不同CUDA版本感到非常困惑nvidia-smi.
我的ubuntu 16.04上安装了cuda9.2和cuda10.现在我将PATH设置为指向cuda9.2.所以当我跑:
$ which nvcc
/usr/local/cuda-9.2/bin/nvcc
但是,当我跑
$ nvidia-smi
Wed Nov 21 19:41:32 2018
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.72 Driver Version: 410.72 CUDA Version: 10.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 106... Off | 00000000:01:00.0 Off | N/A |
| N/A 53C P0 26W / N/A | 379MiB / 6078MiB | 2% …是否可以在同一节点上编译CUDA程序而不使用支持CUDA的设备,仅使用NVIDIA CUDA Toolkit ......？
当我运行“torch.rand(10).to(“cuda”)”时，我遇到“错误：Torch 未在启用 CUDA 的情况下编译”
GPU：Nvidia RTX 3080 Ti
$nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
$nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85
$conda list
cudatoolkit version : 11.0.221
$conda info
active environment : sw
active env location : /mnt/user2/.conda/envs/sw
shell level : 1
user config file : /mnt/user2/.condarc
populated config files :
conda version : 23.1.0
conda-build version : …