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Performance Analysis Tools for Partitioned Global-Address-Space Programming Models

This talk discusses the motivation for PGAS performance tools, the GASP interface, and the Parallel Performance Wizard. It also explores future directions for improving PGAS performance tool support.

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Performance Analysis Tools for Partitioned Global-Address-Space Programming Models

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  1. Performance Analysis Tools for Partitioned Global-Address-Space Programming Models Adam Leko1, Hung-Hsun Su1, Dan Bonachea2, Max Billingsley III1, Alan D. George1 1 Electrical & Computer Engineering Dept., University of Florida 2 Computer Science Dept., UC Berkeley

  2. Outline of Talk • Motivation for PGAS performance tools and tool interface • High-level overview of GAS tool interface, GASP • Overview and demonstration of Parallel Performance Wizard • Conclusions & Future Work

  3. Performance Tools Motivation • PGAS Models • Offer simple, convenient way to express parallelism • Requires an increase in compiler & runtime sophistication • printf()-style performance tuning doesn’t cut it • Doesn’t scale to large runs (time or parallelism) • Not enough information available to programmer • Need for good PGAS performance tools • Good tools help user productivity • Currently, poor support from existing tools • PGAS models are still relatively new, but… • Tool support requires tight interaction with PGAS implementations • Implementations of same language can vary greatly • Solution: generalized performance tool interface (GASP)

  4. GASP Overview • Global Address Space Performance (GASP) interface • Event-based interface • GAS compiler/runtime communicate with performance tools using standard interface • Performance tool is notified when particular actions happen at runtime • Implementation-agnostic • Notification structure • Function “callback” to tool developer code • Use a single function name (gasp_event_notify) • Notifications can come from compiler/runtime (system events) or from code (user events) • Allows calls to the source language/library to make model-specific queries • Flexible instrumentation methods supported • Formal specification available at http://www.hcs.ufl.edu/upc/gasp/

  5. Parallel Performance Wizard • New performance tool designed for PGAS languages • UPC and SHMEM in particular • GASP interface developed to meet needs of this work • Beta version available:http://www.hcs.ufl.edu/ppw/ • Java WebStart version of GUI available for immediate testing

  6. PPW + GASP Preliminary Overheads UPC version of NAS NPB benchmarks (class “B”) on Berkeley UPC v2.3.16 (32-node Quadrics QsNetII 2.0 GHz Opteron cluster)

  7. What Does This Mean for Users? • Paula the PGAS Programmer just wrote an application in UPC • Performance issues, wants to know why • Before: printf() & grep / perl • Now: PPW • Demo time!

  8. Vendor Support • UPC • Berkeley UPC • GASP implemented within runtime library • Supported with Berkeley UPC 2.3.16 • --enable-profile configure-time option • Other UPC implementations • GASP support pending • Other PGAS model implementations • Titanium & SHMEM GASP support is inthe pipeline • Spec definitions for otherlanguages/libraries forthcoming

  9. Conclusions & Future Directions • Conclusions • GASP interface initial implementation overhead results promising (validate approach) • PPW shows usefulness of fine-grained performance data • Interface can be helpful for advanced end-users • Future directions • Help add GASP support to other PGAS language implementations • Extend GASP to support other models (CAF, …) • Help other tools take advantage of GASP support • For more information on PPW and GASP, please see • http://www.hcs.ufl.edu/upc/gasp/ • http://www.hcs.ufl.edu/ppw/ • Beta testers encouraged for PPW!

  10. Q&A

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