- CUDA和对应的driver的兼容性
google : cuda x.x.x driver Compatible 查文档
https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility
Table 1. CUDA Toolkit and Compatible Driver Versions
CUDA Toolkit Linux x86_64 Driver Version
CUDA 11.0 (11.0.171) >= 450.36.06
CUDA 10.2 (10.2.89) >= 440.33
CUDA 10.1 (10.1.105 and 10.1.243) >= 418.39
CUDA 10.0 (10.0.130) >= 410.48
CUDA 9.2 (9.2.88) >= 396.26
CUDA 9.1 (9.1.85) >= 390.46
CUDA 9.0 (9.0.76) >= 384.81
CUDA 8.0 (8.0.61 GA2) >= 375.26
CUDA 8.0 (8.0.44) >= 367.48
CUDA 7.5 (7.5.16) >= 352.31
CUDA 7.0 (7.0.28) >= 346.46
Note: Driver没有sudo权限很麻烦， 而cuda可以自己随便装
- CUDA与GCC的兼容性
https://stackoverflow.com/a/46380601/7701908
| CUDA version | max supported GCC version |
|---|---|
| 11 | 9 |
| 10.1, 10.2 | 8 |
| 9.2, 10.0 | 7 |
| 9.0, 9.1 | 6 cuda9.0不支持GCC 6.0.1 |
| 8 | 5.3 |
| 7 | 4.9 |
| 5.5, 6 | 4.8 |
| 4.2, 5 | 4.6 |
| 4.1 | 4.5 |
| 4.0 | 4.4 |
CUDA, GCC, Driver三者中，CUDA最容易控制，随意利用Driver，GCC的版本，查表选择需要的cuda。
而对应的cuda还需要有cuda对应的pytorch
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