Question

我有以下测试代码：

    import tensorflow as tf
import numpy as np

def body(x):
    a = tf.random_uniform(shape=[2, 2], dtype=tf.int32, maxval=100)
    b = tf.constant(np.array([[1, 2], [3, 4]]), dtype=tf.int32)
    c = a + b
    return tf.nn.relu(x + c)

def condition(x):
    return tf.reduce_sum(x) < 100

x = tf.Variable(tf.constant(0, shape=[2, 2]))

with tf.Session():
    tf.initialize_all_variables().run()
    result = tf.while_loop(condition, body, [x])
    print(result.eval())

当我在GPU群集上运行它时，我产生以下错误：

2018-03-30 18:10:33.473913: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10415 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:3d:00.0, compute capability: 6.1)
2018-03-30 18:10:33.591203: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 10415 MB memory) -> physical GPU (device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:3e:00.0, compute capability: 6.1)
2018-03-30 18:10:33.688390: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:2 with 10415 MB memory) -> physical GPU (device: 2, name: GeForce GTX 1080 Ti, pci bus id: 0000:60:00.0, compute capability: 6.1)
2018-03-30 18:10:33.806845: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:3 with 10415 MB memory) -> physical GPU (device: 3, name: GeForce GTX 1080 Ti, pci bus id: 0000:61:00.0, compute capability: 6.1)
2018-03-30 18:10:33.913200: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:4 with 10415 MB memory) -> physical GPU (device: 4, name: GeForce GTX 1080 Ti, pci bus id: 0000:b1:00.0, compute capability: 6.1)
2018-03-30 18:10:34.018533: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:5 with 10415 MB memory) -> physical GPU (device: 5, name: GeForce GTX 1080 Ti, pci bus id: 0000:b2:00.0, compute capability: 6.1)
Killed

当我使用CUDA_VISIBLE_DEVICES='6' python script.py运行脚本时，它会使用GPU中止。可能是什么导致了这个？这可能是一个有缺陷的GPU吗？

nvidia-smi报告以下内容：

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 390.25                 Driver Version: 390.25                    |
|-------------------------------+----------------------+----------------------+
| 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 108...  Off  | 00000000:3D:00.0 Off |                  N/A |
| 28%   21C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 108...  Off  | 00000000:3E:00.0 Off |                  N/A |
| 28%   21C    P8     7W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  GeForce GTX 108...  Off  | 00000000:60:00.0 Off |                  N/A |
| 28%   24C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  GeForce GTX 108...  Off  | 00000000:61:00.0 Off |                  N/A |
| 28%   25C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   4  GeForce GTX 108...  Off  | 00000000:B1:00.0 Off |                  N/A |
| 28%   19C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   5  GeForce GTX 108...  Off  | 00000000:B2:00.0 Off |                  N/A |
| 28%   20C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   6  GeForce GTX 108...  Off  | 00000000:DA:00.0 Off |                  N/A |
| 28%   22C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   7  GeForce GTX 108...  Off  | 00000000:DB:00.0 Off |                  N/A |
| 28%   21C    P8     8W / 250W |      0MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

Tensorflow版本为1.7.0，CUDA版本为9.0.176

Answer 1

问题是创建作业以使用那么多GPU时，我没有请求足够的RAM空间。要使用8个GPU，您需要足够的空间，也许大约60 Gi。

Tensorflow无法在太多GPU上运行代码？

1 个答案: