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updating to latest name for docker images

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Beth Dean
2018-12-04 14:13:25 -08:00
parent 88ce699f98
commit b4aa772811
1 changed files with 11 additions and 20 deletions
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source/clear-linux/tutorials/dlaas-benchmarks.rst
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@@ -19,7 +19,7 @@ Prerequisites
* `cloud-native-basic` bundle is installed (includes kubernetes)
In |CL|, `containers-basic` provides Docker*, which is required for
TensorFlow benchmarking. Use the :command:`swupd` utility to check if
TensorFlow benchmarking. Use the :command:`swupd` utility to check if
`containers-basic` and `cloud-native-basic` are present:
.. code-block:: bash
@@ -37,23 +37,16 @@ To ensure that kubernetes is correctly installed and configured,
We have validated these steps against the following software package versions
* |CL| 26240--lowest version permissible.
* Docker 18.06.1
* Kubernetes 1.11.3
* Go 1.11.12
TensorFlow benchmarks
=====================
The |CL| Deep Learning Stack is available in two versions. First, a version that includes TensorFlow* optimized for Intel Architecture, the `Eigen`_ version, and a version that includes the TensorFlow* framework optimized using Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) primitives, the `Intel MKL`_ version.
This section describes running the `TensorFlow benchmarks`_ as run by the
TensorFlow community. These steps provide a template to run other
benchmarks, providing they can invoke TensorFlow.
TensorFlow* Single and Multi Node Benchmarks
============================================
The |CL| Deep Learning Stack is available in two versions:
This section describes running the `TensorFlow benchmarks`_ in single node. For multi node testing replicate these steps for each node. These steps provide a template to run other benchmarks, providing they can invoke TensorFlow.
Download and run either the `Eigen`_ or the `Intel MKL-DNN`_ docker image from hub.docker.com. The next commands will take place in the running container. Replace <docker_name> with the name of the image.
* `TensorFlow`_ includes TensorFlow optimized for Intel® architecture
* `TensorFlow with MKL-DNN`_ includes the TensorFlow* framework optimized
using Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN)
Download and run either of these from the `Clear Linxu Docker Hub page`_.
The next commands will take place in the running container.
@@ -79,8 +72,8 @@ The next commands will take place in the running container.
You can replace the model with one of your choice supported by the
TensorFlow benchmarks.
Kubeflow benchmarks
===================
Kubeflow Multinode benchmarks
=============================
The benchmark workload will run in a Kubernetes container. We will use Kubeflow and deploy three nodes for this tutorial to get a decent return.
@@ -209,12 +202,10 @@ benchmark results.
.. _flannel: https://github.com/coreos/flannel
.. _networking documentation: https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/#pod-network
.. _quick start guide: https://www.kubeflow.org/docs/started/getting-started/
.. _TensorFlow: https://hub.docker.com/r/clearlinux/stacks-dlaas-oss/
.. _TensorFlow with MKL-DNN: https://hub.docker.com/r/clearlinux/stacks-dlaas-mkl/
.. _Eigen: https://hub.docker.com/r/clearlinux/stacks-dlaas-oss/
.. _Intel MKL-DNN: https://hub.docker.com/r/clearlinux/stacks-dlaas-mkl/
.. _release notes for the Clear Linux Deep Learning Stack: https://github.com/clearlinux/dockerfiles/tree/master/stacks/dlaas
.. _Clear Linux Docker Hub page: https://hub.docker.com/u/clearlinux/