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SURA GridPlan Infrastructure Working Group Art Vandenberg Georgia State University Mary Fran Yafchak SURA Working.

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Presentation on theme: "SURA GridPlan Infrastructure Working Group Art Vandenberg Georgia State University Mary Fran Yafchak SURA Working."— Presentation transcript:

1 SURA GridPlan Infrastructure Working Group Art Vandenberg Georgia State University avandenberg@gsu.edu Mary Fran Yafchak SURA maryfran@sura.org Working Group Co-leads:

2 March 22, 20052/19 Infrastructure WG Charter Primary Goal: Build a regional grid or interconnection of semi-regional grids capable of supporting activities that advance the availability of Grid infrastructure to SURA member institutions.

3 March 22, 20053/19 Infrastructure WG Charter Specific Activities: Increase the number and diversity of interconnected nodes and their availability to researchers. Expand secure grid authentication between institutions, including diverse local CAs & BridgeCA in alignment with national & international directions. Implement grid services and tools, and evaluation of these, within a test environment of actual nodes and applications.

4 March 22, 20054/19 Infrastructure WG Charter Specific Activities: Develop new network monitoring, measurement and performance tools available to grid applications and users. Investigate policy and entry procedures for shared inter-institutional grids & recommend best practices. Investigate models to open grid resources to broader user communities (e.g. teaching faculty, students).

5 March 22, 20055/19 SURAgrid as Foundation Evolved from the NMI Testbed Grid, initiated by SURA in September 2003 as part of the NSF Middleware Initiative (NMI) Integration Testbed Program –http://www.nsf-middleware.org/testbed/testbed_status.asp#grid Goal is a scalable infrastructure that leverages local institutional identity and authorization while managing access to shared resources across organizational boundaries. –Working to build the grid without over-specifying the technology –Enabling inter-institutional access that is “seamless” for users and realistic (interoperable, scalable) for the grid –Fostering the sharing and development of real applications to proof the infrastructure while bringing recognizable value to users

6 March 22, 20056/19 SURAGrid: participants… from May 2004 GSU UAH UAB UMICH UVA USC TACC Louisiana TAMU UFL OleMiss GMU Tulane UARK TTU SC LSU GPN

7 March 22, 20057/19 SURAgrid Resources

8 March 22, 20058/19 Application Example 1 Genome Alignment Algorithm 1. Researcher: Nova Ahmed, PhD Student, Georgia State University 2. Application Goal: Analysis of genome alignment performance across clusters and grids 3. Value of sharing: Access to resources not available at home institutions 4. Participating Institutions: GSU, UAB, USC, TACC, UVA

9 March 22, 20059/19 Sequence alignment Sequences used to find biologically meaningful relationships among organisms –Evolutionary info; diseases, causes, cures –Finding out information about proteins Compute intensive for long sequences –Needleman & Wunsch (1970) - optimal global alignment –Smith & Waterman (1981) - optimal local alignment –Taylor (1987) - multiple alignment by pairwise alignment –BLAST trades optimal results for faster computation Challenge - achieve optimal results without sacrificing speed

10 March 22, 200510/19 Parallel distribution of multiple sequences Sequences 1-6 Sequences 7-12 Seq 1-2 Seq 5-6 Seq 3-4

11 March 22, 200511/19 Computation Time potential for multiple clusters across grid?

12 March 22, 200512/19 Run @ UVA using UAB cert (BridgeCA)

13 March 22, 200513/19 Application Example 2 Task-Farming for Black Hole Simulation 1.Researcher: Rion Dooley, IT Analyst, CCT 2.Application Goal: Faster calculation for “grand scale” parameter survey 3.Value of sharing: Unattended, opportunistic use of computational resources across institutions 4.Participating Institutions: LSU, TACC, UVA*, UAB* *via BridgeCA

14 March 22, 200514/19 Task Farming Certain classes of problems require large numbers of nearly identical runs to produce meaningful results. Examples: –Monte-Carlo simulations –Smith-Waterman analyses –Data mining –Parameter sweeps Task farming is a way to utilize multiple resources to solve such problems.

15 March 22, 200515/19 Task Farm Infrastructure Using general Task Farming infrastructure written using Cactus –Hierarchy of “Task Farm Managers (TFM)” –Pluggable components to easily use different technologies (e.g. GAT) –Grid enabled and very portable –Supports task scheduling Can handle needs of different classes of applications by adding new “Logic Managers” –Fill out simple API for general task farming (how to start application, provide parameter file, etc) Application independent –no need to recompile existing application –Generic Logic Manager can be used for most apps

16 March 22, 200516/19 Task Farm Infrastructure Grid functionality provided through the Grid Application Toolkit (GAT) –Resource discovery –Job submission –File transfer Using GAT means many different technologies/services can be used http://www.gridlab.org/GAT

17 March 22, 200517/19 Task Monitoring Task Farming infrastructure can make use of our other tools, e.g. –HTML interface to monitor the progress of the overall tasks and to steer individual TFM’s* –Portal interface to start, stop, and track tasks

18 March 22, 200518/19 Future of TFI and SURA Grid Explore new ways to schedule and share resources with SURA Grid –User-centric vs. resource-centric resource allocation –Dynamic resource scheduling based on “good neighbor” policies

19 March 22, 200519/19 Sample Run: Black Hole Simulation Parameter Survey


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