这不是真的:"A conda package of Intel's optimized Tensorflow comes with the new 2018 Intel Python distrib



在以下网页上:

https://software.intel.com/en-us/articles/intel-optimized-tensorflow-wheel-now-available

据称:"英特尔优化的Tensorflow的conda软件包附带了2018年新的英特尔Python Linux发行版。">

我觉得这不是真的。


在我们的集群上,我们有:

英特尔并行工作室XE 2018

在单独的安装中,我们获得了:

英特尔Python部署(IDP)2018(2.7,3.6).


以下是一个屏幕截图,其中包含优化的tensorflow没有随IDP 2018一起提供的证据:

[whowell@acf-knl004 ~]$ module load intel-python/2.7/2018.0.018
[whowell@acf-knl004 ~]$ which python
/global/opt/intel/python/2018.0.018/intelpython2/bin/python
[whowell@acf-knl004 ~]$ python -c 'import tensorflow as tf;print          
tf.__file__;sess = tf.InteractiveSession()'
/global/opt/intel/python/2018.0.018/intelpython2/lib/python2.7/site-   
packages/tensorflow/__init__.pyc
2017-10-09 18:28:23.284004: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library 
wasn't compiled to use SSE4.1 instructions, but these are available on your 
machine and could speed up CPU computations.
2017-10-09 18:28:23.284243: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library 
wasn't compiled to use SSE4.2 instructions, but these are available on your 
machine and could speed up CPU computations.
2017-10-09 18:28:23.284311: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library 
wasn't compiled to use AVX instructions, but these are available on your 
machine and could speed up CPU computations.
2017-10-09 18:28:23.284456: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library     
wasn't compiled to use AVX2 instructions, but these are available on your 
machine and could speed up CPU computations.
2017-10-09 18:28:23.284518: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library 
wasn't compiled to use AVX512F instructions, but these are available on your 
machine and could speed up CPU computations.
2017-10-09 18:28:23.284579: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library 
wasn't compiled to use FMA instructions, but these are available on your 
machine and could speed up CPU computations.

其中一个优化是使用矢量指令进行构建。因为我们收到一个警告,使用的tensorflow不是用矢量指令构建的,所以我们不能使用优化版本。


我们有大型分布式tensorflow运行的生物信息学家,以及专门为此目的的新KNL。至关重要的是,我们从KNL的优化张量流开始。我们的员工中有一些人在Xeon Phi架构和NVIDIA GPU方面拥有多年的前沿研究经验。未来很可能会有合作的机会,以扩展tensorflow产品。


你建议我们下一步做什么?

我们非常感谢在这方面提供的任何协助。

Dr。Mitch Horton联合计算科学研究所田纳西大学,田纳西州诺克斯维尔

警告可能不合法。原因是有两种方法可以使二进制文件使用特定于体系结构的指令。

  1. 修复一个体系结构,并使用体系结构特定的标志构建一切(谷歌方式)

  2. 使用动态调度来选择运行时可用于体系结构的最佳指令。(世界其他地方的方式)

警告只检查方式1。它们无法判断英特尔的操作是否使用动态调度逻辑来自动选择适合体系结构的最佳指令。

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