S oftware T ools for A cademics and R esearchers MASSACHUSETTS INSTITUTE OF TECHNOLOGY Office of...

Software Tools for Academics and Researchers http://web.mit.edu/starMASSACHUSETTS INSTITUTE OF TECHNOLOGY

Office of Educational Innovation and Technology

StarCluster

Justin Riley ([email protected])

Software Tools for Academics and ResearchersOffice of Educational Innovation and Technology

Massachusetts Institute of Technology77 Massachusetts Ave.Cambridge, MA 02139

HPC on Amazon's Elastic Compute Cloud

(http://web.mit.edu/starcluster)



Outline About STAR Overview of Amazon Web Services (AWS) Elastic Compute Cloud (EC2) Hardware Motivations Behind StarCluster About StarCluster StarCluster Features StarCluster Advantages StarCluster Live Demo EC2 Performance Materials Science Research Case Study



About STARWhat's your biggest problem bringing your research into the classroom?



Elastic Compute Cloud (EC2) Features:

Amazon EC2 allows you to dynamically allocate and terminate Linux “virtual” machines with a variety of hardware configurations

Pay only for what you use (i.e. machine hours and data transfer)

Ability to capture software configurations into Amazon Machine Images (AMI) for later use.

AMI's can be used to launch multiple machines with identical software configurations.

Overview of



Elastic Block Storage (EBS) Features:

EBS volumes are highly available, highly reliable volumes that can be attached to a running Amazon EC2 machine and are exposed as standard block devices

Allows you to create point-in-time snapshots of your data.

Pay per month based on allocation as well as per 1 million I/O requests ($0.10/GB allocated/month and $0.10/million I/O requests)

1GB-1TB limit per EBS volume

Overview of



Elatic Compute Cloud Hardware

Instance Arch CPU RAM Storage I/O Performance Cost/hr

Small 32bit 1.0-1.2GHz 1.7GB 160GB Moderate $0.10/hr

Large 64bit 2.0-2.4GHzdual-core

7.5GB 860GB High $0.40/hr

Extra Large 64bit 2.0-2.4GHz quad-core

15GB 1.690TB High $0.80/hr

Instance Arch CPU RAM Storage I/O Performance Cost/hr

Medium 32bit 2.5-3.0GHzdual-core

1.7GB 350GB Moderate $0.20/hr

Extra Large 64bit 2.5-3.0GHzquad-core(ht)

7GB 1.690TB High $0.80/hr

Standard Instances

High CPU Instances

One EC2 Compute Unit provides the equivalent CPU capacity of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor.



Motivations Behind StarCluster

StarHPC - an on demand compute cluster for parallel programming with both OpenMP and OpenMPI technologies. It provides a virtual desktop environment, hosted on EC2, configured with all the necessary tools for programming in OpenMP/OpenMPI.

http://web.mit.edu/star/hpc

StarMolsim - a web application used to run materials modeling research software. It enables the user to run various simulations on a distributed compute cluster and retrieve the results, all from a web browser.

http://web.mit.edu/star/molsim



HPC in the Classroom

Constantinos Evangelinos,PhD

Researcher in Earth, Atmospheric, and Planetary Sciences.

Nicola Marzari, PhD

Associate Professor in Computational Materials Science

Markus Buehler, PhD

Assistant Professor in Civil and Environmental Engineering

Materials Modeling Parallel Programming



StarHPCUse case: students have direct access to a HPC cluster to actively develop parallel programs using the Message Passing Interface (MPI)

StarHPC was used for 2 weeks in an Independent Activities Period (IAP) course for parallel programming using OpenMP and OpenMPI.

Result: Creating a 4-node cluster for two weeks came out to about $25 per student using Amazon EC2.

SSH/VNC

Virtual Desktop EnvironmentEC2 OpenMPI ClusterUser



StarMolsimUse case: students log in to a web application as a proxy to the computing resources. The web application handles communicating with the cluster to submit jobs, retrieve the results, etc.

Result: Amazon EC2 was used to replace a traditional 9-node HPC cluster for an entire semester. The cost for using the 9 node EC2 cluster for the semester was around $3,000-$4,000.

UserEC2 Cluster

Web Server hosting GenePattern from the Broad Institute of MIT and Harvard



About StarCluster

http://web.mit.edu/stardev/cluster

StarCluster is a utility for creating and managing general purpose compute clusters hosted on Amazon's Elastic Compute Cloud (EC2).

StarCluster makes it easy for a user to create their own compute cluster on EC2 and pay only for what they use.

Software included in the virtual machine: OpenMPI NFS'd /home directory Sun Grid Engine Scipy/Numpy/IPython Compilers for installing your own custom software Ubuntu Linux OS with apt-get for installing additional OS software

StarCluster Dependencies: Registered and fully configured EC2 account. Python 2.4+ Paramiko library for Python



StarCluster Features

• Simple configuration with sensible defaults

• One command to create and configure a n-node cluster on EC2

• Utilizes Amazon's Elastic Block Storage to store and

snapshot your applications and data. • Easily recreate identical working environments

• 32bit/64bit Ubuntu 9.04 public AMI's



StarCluster Features

• Automatic Configuration of:

o Sun Grid Engine with Parallel Environment (PE)

o OpenMPI with SGE PE Support

o NFS shares (e.g. /home and /opt)

o Passwordless SSH

o ~147GB local scratch space on /scratch for each node



StarCluster Advantages• Portable, launch a cluster from virtually anywhere!

• Supplements existing resources when needed

• Easily store your applications and data in the cloud via EBS. Simply upload your applications/data to /home and your data will be available each time you launch StarCluster.

• Easy to install additional OS software. Just launch the AMI, use the package manager to install additional software, and rebundle the AMI to create your own customized version of StarCluster

• Easily package results of computational experiment for reproducible research



StarCluster Live Demo



EC2 PerformanceSummary:

Message Passing – extremely poor in comparison to local HPC resources.

Embarrassingly Parallel – much better, but still under performs compared to local HPC resources.

Walker, E. (2008, October) benchmarking Amazon EC2 for high-performance scientific computing.

Retrieved from http://www.usenix.org/publications/login/2008-10/openpdfs/walker.pdf



Materials Science Case Study54 relaxation calculations, 25 and 32 atoms (C,N,O,H), standard convergence criterion (Espresso-4.0.5 with MKL 10 and gfortran/gcc 4.3.3)

Worst : 53%Best : 57%

Worst : 58%Best : 69%

Worst Best

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CPU Time on a 4 node (c1.xlarge) EC2 Cluster

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Worst Best

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Wall Time on a 4 node (c1.xlarge) EC2 Cluster

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Getting Started with StarCluster

Point your web browser to http://web.mit.edu/starcluster



AWS Funding Opportunities...

Teaching Grants for educators using AWS in courses (plus access to selected course content resources)

Research Grants for academic researchers using AWS in their work

Project Grants for student organizations pursuing entrepreneurial endeavors; Tutorials for students that want to use AWS for self-directed learning

Solutions for university administrators looking to use cloud computing to be more efficient and cost-effective in the university's IT Infrastructure

http://aws.amazon.com/education/

The AWS in Education program offers:

Learn more about AWS in Education programs:



Acknowledgements

Professor Buehler (MIT)

Professor Marzari (MIT)

Constantinos Evangelinos (MIT)

Nicolas Poilvert

Nicolas Pinto (MIT)

Amazon Web Services



Thanks for coming!

Any questions?

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