什么是XLA_GPU和XLA_CPU for tensorflow

Question

我可以列出gpu设备唱下面的tensorflow代码:

import tensorflow as tf
from tensorflow.python.client import device_lib
print device_lib.list_local_devices()

结果是:

[name: "/device:CPU:0"
 device_type: "CPU"
 memory_limit: 268435456
 locality {
 }
 incarnation: 17897160860519880862, name: "/device:XLA_GPU:0"
 device_type: "XLA_GPU"
 memory_limit: 17179869184
 locality {
 }
 incarnation: 9751861134541508701
 physical_device_desc: "device: XLA_GPU device", name: "/device:XLA_CPU:0"
 device_type: "XLA_CPU"
 memory_limit: 17179869184
 locality {
 }
 incarnation: 5368380567397471193
 physical_device_desc: "device: XLA_CPU device", name: "/device:GPU:0"
 device_type: "GPU"
 memory_limit: 21366299034
 locality {
   bus_id: 1
   links {
     link {
       device_id: 1
       type: "StreamExecutor"
       strength: 1
     }
   }
 }
 incarnation: 7110958745101815531
 physical_device_desc: "device: 0, name: Tesla P40, pci bus id: 0000:02:00.0, compute capability: 6.1", name: "/device:GPU:1"
 device_type: "GPU"
 memory_limit: 17336821351
 locality {
   bus_id: 1
   links {
     link {
       type: "StreamExecutor"
       strength: 1
     }
   }
 }
 incarnation: 3366465227705362600
 physical_device_desc: "device: 1, name: Tesla P40, pci bus id: 0000:03:00.0, compute capability: 6.1", name: "/device:GPU:2"
 device_type: "GPU"
 memory_limit: 22590563943
 locality {
   bus_id: 2
   numa_node: 1
   links {
     link {
       device_id: 3
       type: "StreamExecutor"
       strength: 1
     }
   }
 }
 incarnation: 8774017944003495680
 physical_device_desc: "device: 2, name: Tesla P40, pci bus id: 0000:83:00.0, compute capability: 6.1", name: "/device:GPU:3"
 device_type: "GPU"
 memory_limit: 22590563943
 locality {
   bus_id: 2
   numa_node: 1
   links {
     link {
       device_id: 2
       type: "StreamExecutor"
       strength: 1
     }
   }
 }
 incarnation: 2007348906807258050
 physical_device_desc: "device: 3, name: Tesla P40, pci bus id: 0000:84:00.0, compute capability: 6.1"]

我想知道什么是XLA_GPU和XLA_CPU？

Answer 1

如文档中所述，XLA 代表“加速线性代数”。这是 Tensorflow 相对较新的优化编译器，它可以通过将以前的多个 CUDA 内核合并为一个来进一步加快 ML 模型的 GPU 操作（简化，因为这对您的问题并不重要）。

对于您的问题，我的理解是 XLA 与默认的 Tensorflow 编译器足够分离，它们分别注册 GPU 设备，并且对它们视为可见的 GPU 的约束略有不同（有关更多信息，请参见此处）。查看您运行的命令的输出，看起来 XLA 正在注册 1 个 GPU，而普通 TF 正在注册 3 个。

我不确定您是遇到问题还是只是好奇，但如果是前者，我建议您查看我上面链接的问题和这个问题。Tensorflow 对哪些 CUDA/cuDNN 版本可以完美运行很挑剔，而且您可能使用的是不兼容的版本。（如果您没有问题，那么希望我回答的第一部分就足够了。）