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PyTorch教程6.7之显卡

消耗积分:0 | 格式:pdf | 大小:0.20 MB | 2023-06-05

李鑫

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表 1.5.1中,我们讨论了过去二十年计算的快速增长。简而言之,自 2000 年以来,GPU 性能每十年增加 1000 倍。这提供了巨大的机会,但也表明提供这种性能的巨大需求。

在本节中,我们将开始讨论如何在您的研究中利用这种计算性能。首先是使用单个 GPU,然后是如何使用多个 GPU 和多个服务器(具有多个 GPU)。

具体来说,我们将讨论如何使用单个 NVIDIA GPU 进行计算。首先,确保您至少安装了一个 NVIDIA GPU。然后,下载NVIDIA驱动和CUDA,根据提示设置合适的路径。这些准备工作完成后,nvidia-smi就可以通过命令查看显卡信息了。

!nvidia-smi
Fri Feb 10 06:11:13 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.106.00  Driver Version: 460.106.00  CUDA Version: 11.2   |
|-------------------------------+----------------------+----------------------+
| GPU Name    Persistence-M| Bus-Id    Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap|     Memory-Usage | GPU-Util Compute M. |
|                |           |        MIG M. |
|===============================+======================+======================|
|  0 Tesla V100-SXM2... Off | 00000000:00:17.0 Off |          0 |
| N/A  35C  P0  76W / 300W |  1534MiB / 16160MiB |   53%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  1 Tesla V100-SXM2... Off | 00000000:00:18.0 Off |          0 |
| N/A  34C  P0  42W / 300W |   0MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  2 Tesla V100-SXM2... Off | 00000000:00:19.0 Off |          0 |
| N/A  36C  P0  80W / 300W |  3308MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  3 Tesla V100-SXM2... Off | 00000000:00:1A.0 Off |          0 |
| N/A  35C  P0  200W / 300W |  3396MiB / 16160MiB |   4%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  4 Tesla V100-SXM2... Off | 00000000:00:1B.0 Off |          0 |
| N/A  32C  P0  56W / 300W |  1126MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  5 Tesla V100-SXM2... Off | 00000000:00:1C.0 Off |          0 |
| N/A  40C  P0  84W / 300W |  1522MiB / 16160MiB |   47%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  6 Tesla V100-SXM2... Off | 00000000:00:1D.0 Off |          0 |
| N/A  34C  P0  57W / 300W |  768MiB / 16160MiB |   3%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  7 Tesla V100-SXM2... Off | 00000000:00:1E.0 Off |          0 |
| N/A  32C  P0  41W / 300W |   0MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                 |
| GPU  GI  CI    PID  Type  Process name         GPU Memory |
|    ID  ID                          Usage   |
|=============================================================================|
|  0  N/A N/A   18049   C  ...l-en-release-1/bin/python   1531MiB |
|  2  N/A N/A   41102   C  ...l-en-release-1/bin/python   3305MiB |
|  3  N/A N/A   41102   C  ...l-en-release-1/bin/python   3393MiB |
|  4  N/A N/A   44560   C  ...l-en-release-1/bin/python   1123MiB |
|  5  N/A N/A   18049   C  ...l-en-release-1/bin/python   1519MiB |
|  6  N/A N/A   44560   C  ...l-en-release-1/bin/python   771MiB |
+-----------------------------------------------------------------------------+

在 PyTorch 中,每个数组都有一个设备,我们通常将其称为上下文。到目前为止,默认情况下,所有变量和相关计算都已分配给 CPU。通常,其他上下文可能是各种 GPU。当我们跨多个服务器部署作业时,事情会变得更加棘手。通过智能地将数组分配给上下文,我们可以最大限度地减少设备之间传输数据所花费的时间。例如,在带有 GPU 的服务器上训练神经网络时,我们通常更希望模型的参数存在于 GPU 上。

!nvidia-smi
Fri Feb 10 08:10:21 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.106.00  Driver Version: 460.106.00  CUDA Version: 11.2   |
|-------------------------------+----------------------+----------------------+
| GPU Name    Persistence-M| Bus-Id    Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap|     Memory-Usage | GPU-Util Compute M. |
|                |           |        MIG M. |
|===============================+======================+======================|
|  0 Tesla V100-SXM2... Off | 00000000:00:17.0 Off |          0 |
| N/A  36C  P0  56W / 300W |  1996MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  1 Tesla V100-SXM2... Off | 00000000:00:18.0 Off |          0 |
| N/A  44C  P0  59W / 300W |  2000MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  2 Tesla V100-SXM2... Off | 00000000:00:19.0 Off |          0 |
| N/A  46C  P0  59W / 300W |  1810MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  3 Tesla V100-SXM2... Off | 00000000:00:1A.0 Off |          0 |
| N/A  43C  P0  58W / 300W |   0MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  4 Tesla V100-SXM2... Off | 00000000:00:1B.0 Off |          0 |
| N/A  37C  P0  57W / 300W |  1834MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  5 Tesla V100-SXM2... Off | 00000000:00:1C.0 Off |          0 |
| N/A  49C  P0  60W / 300W |   0MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  6 Tesla V100-SXM2... Off | 00000000:00:1D.0 Off |          0 |
| N/A  44C  P0  59W / 300W |  1842MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+
|  7 Tesla V100-SXM2... Off | 00000000:00:1E.0 Off |          0 |
| N/A  37C  P0  57W / 300W |  1806MiB / 16160MiB |   0%   Default |
|                |           |         N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                 |
| GPU  GI  CI    PID  Type  Process name         GPU Memory |
|    ID  ID                          Usage   |
|=============================================================================|
|  0  N/A N/A   67249   C  ...l-en-release-1/bin/python   1993MiB |
|  1  N/A N/A   67249   C  ...l-en-release-1/bin/python   1997MiB |
|  2  N/A N/A   28134   C  ...l-en-release-1/bin/python   1807MiB |
|  4  N/A N/A   75456   C  ...l-en-release-1/bin/python   1831MiB |
|  6  N/A N/A   75456   C  ...l-en-release-

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