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Add link for launcher.py and note MKL HW reqs for DLRS tutorial. (#570)

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* Add link for launcher.py and note MKL HW reqs for DLRS tutorial.

* Reword note about MKL, change from note to warning.  Closes #560, Closes #559

* Add note specifying Kubeflow v0.4 when using launcher.py
* Closes #559 , Closes #560
This commit is contained in:
Beth Dean
2019-06-28 10:46:25 -07:00
committed by michael vincerra
parent 0070d49b94
commit 45ce94d4df
1 changed files with 12 additions and 3 deletions
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source/clear-linux/tutorials/dlrs/dlrs.rst
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@@ -32,7 +32,7 @@ The Deep Learning Reference Stack is available in the following versions:
* `PyTorch with Intel MKL-DNN`_, which includes PyTorch optimized using Intel®
Math Kernel Library (Intel® MKL) and Intel MKL-DNN.
.. note::
.. important::
To take advantage of the Intel® AVX-512 and VNNI functionality with the Deep
Learning Reference Stack, you must use the following hardware:
@@ -185,6 +185,11 @@ Kubeflow multi-node benchmarks
The benchmark workload runs in a Kubernetes cluster. The tutorial uses
`Kubeflow`_ for the Machine Learning workload deployment on three nodes.
.. warning::
If you choose the Intel® MKL-DNN or Intel® MKL-DNN-VNNI image, your platform must support the Intel® AVX-512 instruction set. Otherwise, an *illegal instruction* error may appear, and you won’t be able to complete this tutorial.
Kubernetes setup
================
@@ -236,9 +241,11 @@ or inject a python script or larger shell script into the container.
Images
======
You must add `launcher.py` to the Docker image to include the Deep
You must add `launcher.py`_ to the Docker image to include the Deep
Learning Reference Stack and put the benchmarks repo in the correct
location. From the Docker image, run the following:
location. Note that this tutorial uses Kubeflow v0.4.0, and cannot guarantee results if you use a different version.
From the Docker image, run the following:
.. code-block:: bash
@@ -486,6 +493,8 @@ Related topics
.. _kubectl overview: https://kubernetes.io/docs/reference/kubectl/overview/
.. _launcher.py: https://github.com/clearlinux/dockerfiles/tree/master/stacks/dlrs/kubeflow
.. _Release notes on Github\*: https://github.com/clearlinux/dockerfiles/blob/master/stacks/dlrs/releasenote.md
.. _Intel® quantization tools: https://github.com/IntelAI/tools/blob/master/tensorflow_quantization/README.md#quantization-tools