您的内核可能是在没有NUMA支持的情况下构建的

时间:2018-08-07 18:18:16

标签: tensorflow linux-kernel numa

我有Jetson TX2,python 2.7,Tensorflow 1.5,CUDA 9.0

Tensorflow似乎正在运行,但是每次运行程序时,都会收到以下警告:

with tf.Session() as sess:

print (sess.run(y,feed_dict)) ...

2018-08-07 18:07:53.200320: E

tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:881] could not open file to read NUMA node: /sys/bus/pci/devices/0000:00:00.0/numa_node

Your kernel may have been built without NUMA support.

2018-08-07 18:07:53.200427: I

tensorflow/core/common_runtime/gpu/gpu_device.cc:1105] Found device 0 with properties:

name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate(GHz): 1.3005 pciBusID: 0000:00:00.0 totalMemory: 7.66GiB freeMemory: 1.79GiB 2018-08-07 18:07:53.200474: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1195] Creating TensorFlow设备(/ device:GPU:0)->(设备:0,名称:NVIDIA Tegra X2, pci总线ID:0000:00:00.0,计算能力:6.2){{ 1}} 2018-08-07 18:07:53.878574: I tensorflow / core / common_runtime / gpu / gpu_device.cc:859]无法将 标识为``NUMA node of /job:localhost/replica:0/task:0/device:GPU:0, defaulting 0。您的内核可能未使用NUMA支持构建。`

我应该担心吗?还是可以忽略不计?

1 个答案:

答案 0 :(得分:2)

这对您来说应该不是问题,因为您不需要此板的NUMA支持(它只有一个内存控制器,因此内存访问是统一的。)

此外,我在nvidia论坛上发现this post似乎证实了这一点。