report on csu hpc (high-performance computing) study ricky yu–kwong kwok co-chair, research...
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Report on CSU HPC (High-Performance Computing)
Study
Ricky Yu–Kwong KwokCo-Chair, Research Advisory Committee
August 18, 2008Presented to CSU CRAD
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Outline
1. Motivation for the Study2. Interpretations of Findings3. Summary of Findings4. Representative HPC Activities5. CoGrid Job Submission System6. HPC Forum (9/3/2008)
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Motivation for the Study
HPC is a 3rd way of conducting research and discovery
To assess current activities and future opportunities
To look at current systems at CSU
To make CSU more competitive in the research arena
Study Motivation
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Interpretations of Findings
37 responses 26 departments, 31 research areas
HPC is “hot” at CSU!
1/3 of users have no immediate access to HPC resources rely on other departments within CSU OR other organizations outside CSU may be subject to strict resource restrictions
Interpretations of Findings
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Interpretations of Findings
Scattered resources
Majority of users pessimistic about their HPC needs being met in future
Advanced visualization needs require enhancement
Need to “advertise” GRAD 510/511 courses
Space limitations for HPC hardware???
Consultancy?
Affinity groups?Interpretations of Findings
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Summary of Findings
37 responses 26 departments, 31 research areasBesides CoGrid node, Bioinformatics cluster and HP Half Dome system, 8 additional HPC resources, e.g., (see Table 2 in the Report) CIRA – 32-processor cluster Chemical and Biological Engineering – 32-node
Linux cluster Mathematics – 42-node cluster Some more new resources to come (e.g., new
HP donations)Summary of Findings
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Usage of HPC
Summary of Findings
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Nature of Usage
Summary of Findings
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Algorithms Used
Summary of Findings
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HPC Resource Used
Summary of Findings
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HPC Needs Met?
Current Future
Summary of Findings
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Visualization Needs Met?
Current Future
Summary of Findings
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Compiler Used
Summary of Findings
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Language Used
Summary of Findings
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Be Involved in Future HPC Activities?
Summary of Findings
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Aware of GRAD 510/511?
Summary of Findings
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Required Follow-Up?
Summary of Findings
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Presentation Outline
1. Motivation of the Study2. Interpretations of Findings3. Summary of Findings4. Representative HPC Activities5. CoGrid Job Submission System6. HPC Forum
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Small-angle X-ray Scattering (SAXS)
To understand biological systems
Determine 3-D structure
Monte Carlo simulations for data modeling
Computationally intensive HPC
Representative HPC Activities
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Genomic Analysis
Study the evolution of functional DNA sequences
Comparative phylogenomic analysis
Highly computationally intensive cluster of Linux machines with 8 – 32 nodes
Representative HPC Activities
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Proteomics
Large-scale study of proteins
Searching methods to analyze mass spectrometry data
Sequence matching
Access to large databases
Representative HPC Activities
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Pattern Analysis
Investigate unexplained phenomena from high-dimensional, massive data sets
Mathematical theory efficient algorithms exploring, understanding, modeling massive data sets
PAL lab (Pattern Analysis Laboratory)
42-node cluster with 156 GB total memory, over 5 TB disk storage
Representative HPC Activities
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CoGrid Job Submission System
Sharing of geographically distributed computational resources
Batch processing of jobs Job description Resource requirements Execution Monitoring
CoGrid
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HPC Forum (9/3/2008)
1. Introduction and ISTeC Overview: HJ
2. Background on CSU’s HPC History and Activities: Pat Burns
3. Findings from ISTeC’s HPC Survey: Ricky
4. Advanced Networking Capabilities at CSU: Scott Baily, Director of ACNS
5. Educational Activities in HPC: Sanjay Rajopadhye and Wim Bohm (Computer Science)
6. Plan for an ISTeC Visualization Facility: HJ
7. NERSC and the INCITE Program as a Viable Alternative: Josh Ladd (Mathematics)
8. Open Discussion – Faculty Needs and Directions
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Summary
Motivation: To look at current systems in CSU and future HPC needs
Presented interpretations and findings of the survey
Discussed representative HPC activities
Introduced CoGrid job submission system, as a possible campus-wide resource management model
HPC Forum for further discussions