An Introduction to High Performance Computing in the Department

An Introduction to High Performance Computing

in the Department

Ashley Ford & Chris Jewell

Department of Statistics University of Warwick

1 Some Background

2 _{How is Buster used?}

3 Software

Outline

1 Some Background

2 How is Buster used?

3 Software

What is Buster for?

Raw computing power:

Large datasets → lots ofmemory

Complex algorithms →fast processing

Batch processing

Ability to set your algorithm running, and get on with other work.

Interactivesessions

Manipulating data in real-time.

Cost effectiveness

High-powered centralised computing facility shared among users

System architecture

Internet

Execution

Fileserver Frontend

Specifications

2 x 2.33GHz Intel E5410 Quad Core processors 8GB fully buffered RAM

Storage Cluster

LustreTM high performance filesystem

17TB RAID storage

Execution Nodes(11 machines, 108 CPUs)

5 nodes: 3.16GHz Intel X5460 Quad Core x2, 16GB FBRAM 2 nodes: 2.93GHz Intel X5570 Quad Core x2, 16GB FBRAM 5 nodes: 2.80GHz Intel X5660 Six Core x2, 48GB FBRAM

Outline

1 Some Background

2 How is Buster used?

3 Software

What you get

Standard user accounts provide:

Username (same as ITS username) andpassword

1GB fault-tolerant home storage

Expandable if required

Backed up nightly to ITS central backup service

Default 150GB storagespace.

Fault tolerant NOTbacked up!

Up to 800GB scratchspace, shared with other users

Files deleted automatically after 14 days

Frontend node

Internet

Frontend

Fileserver

Logging in

Login provided over SSH secure shell connection

Hostname: buster.stats.warwick.ac.uk

Provides password-protected access fromanywhere on the

internet.

Graphical forwarding enabled (eg. R graphs, text editors) Clients:

Linux / MacOS X- nativesshclient

Accessing files

SSH

Encryptedfile transfer from anywhere on the internet Usescp(Linux/MacOS X) orWinSCP(Windows)

Windows fileshare

Unencryptedfrom within campus (still requires password, though)

Home: \\buster\<username>

The module system

Software packages available viamodulecommand

Allows versioningof software packages Checks for conflicts between packages

Available packages: module avail

Adding a module (default version): module add R

Adding a module (specific version): module add R/2.8.1

Displaying information: module display R

Submitting jobs

Internet

Execution

Fileserver Frontend

Submitting jobs

Grid Engine

Jobs managed by Grid Engine (Sun/Oracle/Open Grid

Scheduler)

Interactivejobs

Batchjobs

Submit a job from the Frontend node, and Grid Engine sends it to a free slot on an execution node

Interactive jobs

Requested via theqlogincommand on the frontend node

Shortjobs only

eg. running individual commands in R or interactive Python

Pros: interactivity, graphics, quick and simple to use.

Cons: youlose your jobif your connection to Buster is interrupted, lower processor scheduling priority.

Batch Jobs

Submit via a job submission script from the frontend node with qsub:

Ideal for longjobs run in batch mode

Pros:

Allows requests formultiple processors

Provides thetask array facility

Saving standard output and error buffers to disk

Allows you to log out and get on with something else while your job runs

High-priority processor scheduling

Cons:

You have to write a job submission script No interactivity/graphics

Batch Jobs

Example job script - /usr/sge/examples/jobs/r-example.sh

# !/bin/bash #$ -S /bin/bash #$ -o /storage/$USER/r-example.stdout #$ -e /storage/$USER/r-example.stderr #$ -l h vmem=500M,h rt=0 . /etc/profile module add R cd /storage/$USER

time R --vanilla << EOF

x<-runif(100) pdf("R-output.pdf") plot(x) dev.off()

Submitting Jobs

Simply:

$ qsub <path to script>

Queues veryshort 1 hour short 12 hours medium 24 hours long 48 hours unlimited ∞

Batch Jobs

Advanced options

Task arrays - instruct Grid Engine to run N instances of your algorithm

-t 1-N:5 (ie. 1 to N jobs, skip every 5)

Parallel environments

For runningparallelalgorithms only!

Shared memory (smp) or distributed memory (mpi) -pe <smp | mpi> n

Monitoring jobs

Monitoring jobs:

qstat monitors job status

To see how busy the queue is: qstat -u \*

Killing jobs:

qdel deletes jobs

Requires the job number (use qstat)

To kill all your jobs at once: qdel -u <username>

Jul Aug Sep Oct Nov

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40

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Outline

1 Some Background

2 How is Buster used?

3 Software

Available Software

GNU Compiler Collection Sun Java 6 SE SDK

Outline

1 Some Background

2 How is Buster used?

3 Software

Buster Support

Using Buster:

1 Command man pages

2 Web documentation: Dept. Homepage →Intranet → Local IT Info → Cluster

3 Forum: New Forum

4 Sysops: Phil Harvey-Smith & Simon Parkes

Help on specific software:

1 Software package documentation

2 Web documentation (FAQ etc etc)

3 Mailing lists 4 _{Google!!!!!!!!!!!!!}

Buster Forum

http://forums.warwick.ac.uk/wf → Departments → Stats → Buster

A new forum has been set up to :

1 _{provide hints and tips}

2 if you spend a long time finding a solution to a problem,

others might benefit from your answer.

3 make requests for new or upgraded software