HANDS ON: AI/ML plus HPC€¦ · DevOps and SysAdmins – Know their systems and infrastructure –...
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1 HANDS ON: AI/ML plus HPC Craig Gardner, Technical Training Architect Member of OpenHPC Technical Steering Committee [email protected] Alessandro Festa, Senior Product Manager Technical Specialist, AI+ML [email protected]
Transcript of HANDS ON: AI/ML plus HPC€¦ · DevOps and SysAdmins – Know their systems and infrastructure –...
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HANDS ON: AI/ML plus HPC
Craig Gardner, Technical Training ArchitectMember of OpenHPC Technical Steering [email protected]
Alessandro Festa, Senior Product ManagerTechnical Specialist, [email protected]
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Perfect Marriage
Nothing works as well together as:
Machine Learning
Artificial General Intelligence
High Performance Enterprise Computing
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Demonstration Objectives
● We can’t make you data scientists
● We can expose you to industry standards and
movement
● We will give you some interesting experience
● You will have a glimpse into what SUSE can do
for you
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Demonstration Agenda
1) Short Introduction
2) Setup SUSE HPC environment (in an AWS Cloud)
3) Explore MPICH for distributed workloads in HPC
4) Setup JupyterHub in the HPC Cloud
5) Scale the Jupyter Notebook workload with SUSE
HPC
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Short Introduction
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Conflict in the Enterprise
DevOps and SysAdmins
– Know their systems and infrastructure
– Know nothing about Data Science
Data Scientists
Know all about their data, models, and tools
– Know just enough about the systems to be dangerous
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Narrow the Gap
Reduce the headaches for DevOps
Provide an easy environment for Data Scientists
This Demonstration:
– HPC and AI/ML are far bigger than can be fully demonstrated
– This demo is just a glimpse into the Perfect Marriage
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Setup HPC
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Setup SUSE HPC environment (in an AWS Cloud)
● Show AWS servers
– 1 head + 4 compute, all running SLES 15 SP1
● Install HPC Module for SLES
● Setup NIS/NFS
● Create a data scientist user
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Explore MPICH
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Explore MPICH for distributed workloads in HPC
● Message Passing Interface for HPC
● There are other options for workloads
– openmpi, slurm, mvapich
● In this demo, simply give compute nodes some
work via MPI
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JupyterHub
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Setup JupyterHub in the HPC Cloud
● JupyterHub: broad collaboration tool for
Jupyter Notebooks
– Jupyter Notebooks: notations for repeating data science through live
code, equations, and visualizations, guided by inline instructions
● Install and Configure JupyterHub
– Runs on the HPC head node
– Largely based on Python, but other tools expand its functionality, too
– iPython facilitates the means of distributing work
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Jupyter Notebook in HPC
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Scale the Jupyter Notebook workload with SUSE HPC
● Setup standard user, called scientist
● As scientist, run Jupyter Notebook
● As scientist, run Jupyter Notebook with
distributed MPICH and HPC resources
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