当前位置:首页 > 服务端 > Allowing GPU memory growth

Allowing GPU memory growth

By default, TensorFlow maps nearly all of the GPU memory of all GPUs (subject to CUDA_VISIBLE_DEVICES) visible to the process. This is done to more efficiently use the relatively precious GPU memory resources on the devices by reducing memory fragmentation.

In some cases it is desirable for the process to only allocate a subset of the available memory, or to only grow the memory usage as is needed by the process. TensorFlow provides two Config options on the Session to control this.

The first is the allow_growth option, which attempts to allocate only as much GPU memory based on runtime allocations: it starts out allocating very little memory, and as Sessions get run and more GPU memory is needed, we extend the GPU memory region needed by the TensorFlow process. Note that we do not release memory, since that can lead to even worse memory fragmentation. To turn this option on, set the option in the ConfigProto by:

 
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
session = tf.Session(config=config, ...)

The second method is the per_process_gpu_memory_fraction option, which determines the fraction of the overall amount of memory that each visible GPU should be allocated. For example, you can tell TensorFlow to only allocate 40% of the total memory of each GPU by:

 
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.4
session = tf.Session(config=config, ...)

This is useful if you want to truly bound the amount of GPU memory available to the TensorFlow process.

作者:jiu~
来源链接:https://www.cnblogs.com/jiu0821/p/9166281.html

版权声明:
1、Java侠(https://www.javaxia.com)以学习交流为目的,由作者投稿、网友推荐和小编整理收藏优秀的IT技术及相关内容,包括但不限于文字、图片、音频、视频、软件、程序等,其均来自互联网,本站不享有版权,版权归原作者所有。

2、本站提供的内容仅用于个人学习、研究或欣赏,以及其他非商业性或非盈利性用途,但同时应遵守著作权法及其他相关法律的规定,不得侵犯相关权利人及本网站的合法权利。
3、本网站内容原作者如不愿意在本网站刊登内容,请及时通知本站(javaclubcn@163.com),我们将第一时间核实后及时予以删除。





本文链接:https://www.javaxia.com/server/125795.html

标签: out of memory
分享给朋友:

“Allowing GPU memory growth” 的相关文章