您的内核可能是在没有 NUMA 支持的情况下构建的
Your kernel may have been built without NUMA support
我有 Jetson TX2、python 2.7、Tensorflow 1.5、CUDA 9.0
Tensorflow 似乎可以正常工作,但每次我 运行 程序都会收到此警告:
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,</code>pci 总线 id: 0000:00:00.0,计算能力:6.2)<code>
2018-08-07 18:07:53.878574: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:859] 无法将 ``NUMA node of /job:localhost/replica:0/task:0/device:GPU:0, defaulting
识别为
0。您的内核可能没有使用 NUMA 支持构建。`
我应该担心吗?还是可以忽略不计?
这对你来说应该不是问题,因为你不需要对此板的 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。
我有 Jetson TX2、python 2.7、Tensorflow 1.5、CUDA 9.0
Tensorflow 似乎可以正常工作,但每次我 运行 程序都会收到此警告:
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,</code>pci 总线 id: 0000:00:00.0,计算能力:6.2)<code>
2018-08-07 18:07:53.878574: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:859] 无法将 ``NUMA node of /job:localhost/replica:0/task:0/device:GPU:0, defaulting
识别为 0。您的内核可能没有使用 NUMA 支持构建。`
我应该担心吗?还是可以忽略不计?
这对你来说应该不是问题,因为你不需要对此板的 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。