Introduction to HPC resources for BCB 660

Introduction to HPC resources for BCB 660

Nirav [email protected]

mailto:[email protected]

mailto:[email protected]

What is Parallel Computing ? General overview of HPC systems Overview of batch system (and why we need

them) Getting started with Ranger Understanding the default user environment Introduction to modules (and why we need

them) Submitting your first job (and monitoring it) Moving your data in and out of HPC systems Q/A

Topic Coverage

von Neumann Architecture Named after the Hungarian mathematician John

von Neumann who first authored the general requirements for an electronic computer in his 1945 papers.

Since then, virtually all computers have followed this basic design of:

Memory (RAM) Control Unit (CPU) Arithmetic Logic Unit (ALU) Input/Output (Keyboard)

What is computing ?

What does it look like (your computer) ?

Image courtesy Univ. of Washington

Parallel computing: use of multiple processors or computers working together on a common task.

Each processor works on part of the problem Processors can exchange information

What is Parallel Computing?

A good introduction to concepts for parallel programing is at:https://computing.llnl.gov/tutorials/parallel_comp/

Traditional software is written to execute serially i.e. one task at a time running on one CPU

As the size of data (tasks) is increasing we need to utilize multiple CPU’s

Size of data also has implications on how much RAM and disk space is required for the task (we need more RAM or disk that fits on one computer)

Why we need it

HPC systems: Not very different

Image courtesy TACC at Univ of Texas

HPC: High Performance Computing = Super Computing

Node: One self contained computer (many of which are connected together to form a “cluster”)

CPU = Socket = Processor = Cores Interconnect: networking between Nodes

(can be fiber optic, or regular ethernet like your computers) e.g. Infiniband or GigE

Some Terminology (Jargon) of HPC

Scalability: Ability to use additional resources to execute tasks faster

Embarrassingly Parallel: Data Parallel tasks where each task is independent and not much communication or coordination is required among tasks

Observed Speedup: “wall time” taken for serial task divided by wall time for parallel task

More Terminology (Jargon) of HPC

Shared memory All CPU (processors) have access to shared RAM

Distributed memory Each CPU (processor) has its own local memory,

but can be connected to others nodes via fast interconnect

Types of HPC

Limits of single CPU computing Performance Available memory (Disk and RAM)

Parallel computing allows one to: Execute Tasks that don’t fit on a single CPU Complete tasks in a reasonable time

Again Please check: https://computing.llnl.gov/tutorials/parallel_comp/

for basic intro to parallel computing concepts

Again why do we need it ?

https://computing.llnl.gov/tutorials/parallel_comp/



Compute power 504 Teraflops 3,936 four socket nodes 62,976 cores, 2.0 GHz AMD Opteron

Memory 125Terabytes 2GB/core, 32 GB/node

Disk subsystem 1.7 PB Storage (Lustre Parallel File System) 1 PB in /work filesystem

Interconnect 8 Gb/s InfiniBand

Lonestar and others machines have similar (much larger specs)

RANGER

HOME Store your source code and build your executables here Use $HOME to reference your home directory in scripts

WORK Store large files here This file system is NOT backed up, use $ARCHIVE for important

files! Use $WORK to reference this directory in scripts

SCRATCH Store large input or output files here – TEMPORARILY This file system is NOT backed up, use $ARCHIVE for important

files! Use $SCRATCH to reference this directory in scripts

ARCHIVE Massive, long-term storage and archive system Check with staff before using this on your account

Filesystem Access

Limits on your filesystem

How is it connected

Please visit the TACC new user guide for RANGER

You will pick up many hints that will make your life MUCH easier for running tasks on TACC resources

http://www.tacc.utexas.edu/user-services/user-guides/ranger-user-guide

http://goo.gl/0xyN5 (same as above)

MUST READ THIS




http://goo.gl/0xyN5

http://goo.gl/0xyN5

With multiple users we need a way to organize tasks

We need a way to assign suitable resources to the tasks (track, prioritize)

With multiple software we need a way to deal with conflicts in version and dependency per tasks

Batch scheduler user on all TACC systems is SGE (Sun Grid Engine) now owned by Oracle.

Batch, Module system

Batch submission

RANGER: Queue Options

Common SGE commands

Lets get working

ssh [email protected]

Module Commands

Compbio stack/modules

Modules are for global use, hard to get cutting edge code as modules (limited staff time)

You can always compile and use your own versions without waiting for a module to be built

When possible, build your applications from source rather than running pre-compiled binaries

If you choose to use “make Install”, you will need to modify the “configure” script to change where it is installed

./configure --prefix=$HOME/bin For best performance, use the the intel compilers For best compatibility, use the gcc compilers More in “bleeding edge s/w” slide

But my favorite app is …

Number of cores and nodes to use is set with:

#$ -pe Nway 16*M N represents the number of cores to utilize

per node Ranger: 1≤N≤16Lonestar:1≤N≤12

M is the number of nodes to utilize The TOTAL number of cores used is thus:

N*M

Preparing for tasks

Preparing a job submission

Some more SGE options

http://genomics.tacc.utexas.edu/projects/ls4compbio/wiki

http://goo.gl/QYnIo (same url as above just short)

Lets look at the tutorial section towards the end of the page

Working with bleeding edge s/w




http://goo.gl/QYnIo

http://goo.gl/QYnIo

Introduction to HPC resources for BCB 660

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