.. title: PAR Class 8, Mon 2020-02-10
.. slug: class08
.. date: 2020-02-10
.. tags: class
.. category: 
.. link: 
.. description: 
.. type: text
.. has_math: true

.. raw:: html

   <style> .red {color:red} </style>
   <style> .blue {color:blue} </style>

.. role:: red
.. role:: blue

.. sectnum::
.. contents:: Table of contents
..


Docker 
------------------

Docker is worth learning, apart from its use by Nvidia for parallel computing.   You might also look up Kubernetes.

#. https://www.docker.com/

#. https://www.zdnet.com/article/what-is-docker-and-why-is-it-so-darn-popular/

#. https://opensource.com/resources/what-docker

On parallel, I think that docker is probably secure, but am not certain.   In return for my allowing access to docker on parallel, I expect you to report, and not to exploit, holes that you might discover.

Compiling:

#. docker run --gpus all -v $PWD:/tmp -it nvcr.io/hpc/pgi-compilers:ce

#. Inside docker:  pcg++ -mp -Minfo=all foo.cc



Nvidia GPU and accelated computing, ctd.
----------------------------------------

This material accompanies **Programming Massively Parallel Processors A Hands-on Approach, Third Edition, David B. Kirk Wen-mei W. Hwu**.  I recommend it.  (The slides etc are free but the book isn't.)

Continuing  /parallel-class/GPU-Teaching-Kit-Accelerated-Computing, Modules 4 to 8.