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Diffstat (limited to 'tensorflow/g3doc/how_tos/using_gpu/index.md')
| -rw-r--r-- | tensorflow/g3doc/how_tos/using_gpu/index.md | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/tensorflow/g3doc/how_tos/using_gpu/index.md b/tensorflow/g3doc/how_tos/using_gpu/index.md index c0bdc5a7cb..8a46c30c95 100644 --- a/tensorflow/g3doc/how_tos/using_gpu/index.md +++ b/tensorflow/g3doc/how_tos/using_gpu/index.md @@ -1,6 +1,6 @@ -# Using GPUs +# Using GPUs <a class="md-anchor" id="AUTOGENERATED-using-gpus"></a> -## Supported devices +## Supported devices <a class="md-anchor" id="AUTOGENERATED-supported-devices"></a> On a typical system, there are multiple computing devices. In TensorFlow, the supported device types are `CPU` and `GPU`. They are represented as @@ -16,7 +16,7 @@ a device. For example, `matmul` has both CPU and GPU kernels. On a system with devices `cpu:0` and `gpu:0`, `gpu:0` will be selected to run `matmul`. -## Logging Device placement +## Logging Device placement <a class="md-anchor" id="AUTOGENERATED-logging-device-placement"></a> To find out which devices your operations and tensors are assigned to, create the session with `log_device_placement` configuration option set to `True`. @@ -46,7 +46,7 @@ MatMul: /job:localhost/replica:0/task:0/gpu:0 ``` -## Manual device placement +## Manual device placement <a class="md-anchor" id="AUTOGENERATED-manual-device-placement"></a> If you would like a particular operation to run on a device of your choice instead of what's automatically selected for you, you can use @@ -78,7 +78,7 @@ MatMul: /job:localhost/replica:0/task:0/gpu:0 [ 49. 64.]] ``` -## Using a single GPU on a multi-GPU system +## Using a single GPU on a multi-GPU system <a class="md-anchor" id="AUTOGENERATED-using-a-single-gpu-on-a-multi-gpu-system"></a> If you have more than one GPU in your system, the GPU with the lowest ID will be selected by default. If you would like to run on a different GPU, you will need @@ -125,7 +125,7 @@ sess = tf.Session(config=tf.ConfigProto( print sess.run(c) ``` -## Using multiple GPUs +## Using multiple GPUs <a class="md-anchor" id="AUTOGENERATED-using-multiple-gpus"></a> If you would like to run TensorFlow on multiple GPUs, you can construct your model in a multi-tower fashion where each tower is assigned to a different GPU. |