NMI Testbed GRIDUtility for Virtual Organization

Art Vandenberg Avandenberg@gsu.edu

Director, Advanced Campus Services Georgia State University

NSF Supported

This material is based in part upon work supported by the National Science Foundation under

Grant No. ANI-0123937 and

Grant No. ITR-0312636.

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

Overview

NMI Testbed GRID – “virtual organization”Participating sitesResources for VO

Catalog of grid applications

Example: genome alignment for VO

Plans for May-August 2004

Vision – NMI Testbed GRID VO

NMI Integration Testbed Program•NSF #ANI-0123937

Explore grid capability – interoperability•Researchers & faculty•Across heterogeneous sites •Integrated with enterprise middleware

A utility grid using NMI components•Non-specialized, open, transparent

Collaborative environment VO

Beyond application specific gridsLeverage enterprise middleware

•Identity management, authN, authZ...•Strive for transparent access

Portals•Ease of use: submit, monitor, retrieve data

Security policy & technology•Federation of cooperating sites

Your Grid is here, now

We want VO utility grid to be here...

Participating sites - the VO

Testbed sites – push interoperation limits

•Georgia State University•Texas Advanced Computing Center•University of Alabama at Birmingham•University of Alabama at Huntsville•University of Michigan•University of Southern California•University of Virginia

Site resources – VO

Testbed sites – interoperation challenges•GSU: Shibboleth, GridPort portal, REU & Grads, disk

•TACC: REU student, portal, Enterprise CA, cluster

•UAB: beowulf cluster, CA, Pubcookie, OGCE portal

•UAH: application expertise, NASA IPG Certs

•UMich: KX.509 & Kerberos, MGrid, ATLAS integration

•USC: CA, Pubcookie, Shibboleth, Linux cluster, KX.509

•UVa: Bridge CA model

Sites non-homogeneous – a VO challenge

Catalog of grid applications

Knowledge base is important•REU students – Nicole Geiger, Anish Shindore

•Graduate Research Asst – Manish Garg

NMI Testbed Sites initially•Researchers, schools, projects•Grid specific as well as grid potential•Started as spreadsheet, now online db

Catalog of grid applications

Catalog of Grid Applications (current version)

http://art12.gsu.edu:8080/grid_cat/index5.jsp

Expanding scope beyond testbed sites•18 schools/labs, 300 researchers & counting

Differentiated from Globus www.gpds.org•Oriented to researcher, institutional level•Planning clustering, visualization modality•Clustering work related to: NSF #ITR-0312636

Example: genome alignment for VO

(GSU – UAB)

An opportunity for utility Grid VO•Nova Ahmed, CS grad with Dr. Yi Pan, GSU•dynamic programming algorithm for genome sequence alignment

Initial runs on GSU shared memory hydra•Limited access (grad student, shared cycles)

•Algorithm improvement using multi-processor cluster across a grid?

The Genome Alignment Problem• Alignment of DNA sequences Sequence X: TGATGGAGGT Sequence Y: GATAGG

• Count the matching score as 1 => matching 0 => non-matching • Populate the Similarity matrix using:

Observation re Similarity Matrix:• Many zero values• Reduction of memory possible by reducing zero value elements

Improved Parallel Algorithmfor Genome Alignment

The new Data Structure: • New algorithm calculates only non-zero values of the similarity matrix• Memory is dynamically allocated as needed

The parallel Method:• Similarity matrix is divided among processors• Processors calculate in parallel to match the partial sequence• Communication is done among the processors to match the whole sequence

Results on the Shared Memory Machine (Hydra)

PerformanceComputation time decreases with increased number of processors

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Computation Time(Shared Memory)

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Limitations• Can not allocate memory for long sequences

Ex: Largest sequence to align is 2000 x 2000

• Number of processors are limited

Ex: For Hydra 12 processors

• Not scalable

Results on the Beowulf Cluster of UAB

Using the beowulf cluster:• Longer genome sequence can be aligned

Highest sequence length can be 10,000 in the cluster

• Limited scalability

Can increase the number of processors up to a certain limit

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Results via the GRID at UAB

Advantages:• Scalable – Can add new clusters to the grid• Easier job submission – Don’t need account on every node• Scheduling is easier – Can submit multiple jobs at one time

Submitting genome alignment program using Globus and MPICH

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Future Work Genome Alignment

Use MPICH-G2 (instead of MPICH) –•Use the power of Grid

Expand the computational resources –•Combine more clusters across the Grid

Develop program to align Multiple Genome Sequences (rather than two at a time) – •Requiring more computation resources

Use Georgia State certificate via Bridge CA•Via Shibboleth protected sector CA…?

Plans for May-August 2004

More resources•Contributed from current sites (others?)

Portal for NMI Testbed GRID•Cf. NPACI Hotpage https://hotpage.npaci.edu/

Integration of campus authN•UVa Bridge CA

More applications•Utility grid for grad research & education

Plans for May-August 2004…

Documentation•Web site•Application docs and demos

Catalog of Grid Applications•Provide for self service contribution•Develop clustering (SOM), visualization options (“find researchers or projects like X”)

•Auto-discovery of Grid researchers & apps based on reference sets (core sites)?

Contact Information

Art Vandenberg•Avandenberg@gsu.edu

NMI Testbed GRID•http://www.gsu.edu/~wwwacs/GRID_Group/NMI.html