gpu ubuntu

ubuntu如何测试gpu性能

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2021-02-02 12:37:43
栏目: 智能运维

ubuntu如何测试gpu性能

ubuntu测试gpu性能的方法:

1.测试系统自动分配设备示例:

#-*- coding:utf-8 -*-

import tensorflow as tf

# 新建一个 graph.

a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')

c = tf.matmul(a, b)

# 新建session with log_device_placement并设置为True.

sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

# 运行这个 op.

print(sess.run(c))

输出如下:

Device mapping:

/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: Tesla K40c, pci bus

id: 0000:05:00.0

b: /job:localhost/replica:0/task:0/gpu:0

a: /job:localhost/replica:0/task:0/gpu:0

MatMul: /job:localhost/replica:0/task:0/gpu:0

[[ 22. 28.]

[ 49. 64.]]

2.测试手动指定分配设备示例:

#-*- coding:utf-8 -*-

import tensorflow as tf

# 新建一个graph.

with tf.device('/cpu:0'):

a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')

c = tf.matmul(a, b)

# 新建session with log_device_placement并设置为True.

sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

# 运行这个op.

print(sess.run(c))

a和b操作都被指派给了cpu:0,输出如下:

Device mapping:

/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: Tesla K40c, pci bus

id: 0000:05:00.0

b: /job:localhost/replica:0/task:0/cpu:0

a: /job:localhost/replica:0/task:0/cpu:0

MatMul: /job:localhost/replica:0/task:0/gpu:0

[[ 22. 28.]

[ 49. 64.]]

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