Towards Automated Tuning of Parallel Programs - PowerPoint PPT Presentation

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Towards Automated Tuning of Parallel Programs

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Title: 1 Author: user Last modified by: hollings Created Date: 8/14/2004 5:45:03 PM Document presentation format: On-screen Show Other titles – PowerPoint PPT presentation

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Title: Towards Automated Tuning of Parallel Programs


1
Towards Automated Tuning of Parallel Programs
  • Jeffrey K. Hollingsworth
  • hollings_at_cs.umd.edu
  • Department of Computer Science
  • University of Maryland, College Park, MD 20742

2
Why Automated Performance Tuning?
  • Software commonly have parameters that impact
    their performance.
  • Optimal parameter values are usually variable and
    un-predictable.
  • Automated Parameter tuning can be used for
    adaptive parameter tuning in complex software.

3
Automated Performance Tuning
  • Goal Maximize achieved performance
  • Problems
  • Large number of parameters to tune
  • Shape of objective function unknown
  • Multiple libraries and coupled applications
  • Analytical model may not be available
  • Requirements
  • Runtime tuning for long running programs
  • Dont try too many configurations
  • Avoid gradients

4
Active Harmony
  • Runtime performance optimization
  • Can also support training runs
  • Automatic library selection (code)
  • Monitor library performance
  • Switch library if necessary
  • Automatic performance tuning (parameter)
  • Monitor system performance
  • Adjust runtime parameters
  • Hooks for Compiler Frameworks
  • Working to integrate USC/ISI Chill
  • Looking at others too

5
Example Cluster Based Web Server
  • 3-tier system
  • Harmony Provides
  • Parameter updates for DB, and App Severs
  • TPC-W Benchmark
  • Transactional web benchmark
  • Mimic operations of an e-commerce site
  • Uses Java implementation from Univ. of Wisconsin
  • Performance metrics
  • Web Interaction Per Second (WIPS)

6
Cluster-Based Web Service Tuning
7
Importance of various parameters
8
A Bit More About Harmony Search
  • Pre-execution
  • Sensitivity Discovery Phase
  • Used to Order not Eliminate search dimensions
  • Online
  • Use Parallel Rank Order Search
  • Different configurations on different nodes

9
Benefits of Searching in Parallel
  • Performance for Two Programs
  • High Performance Linpack
  • POP Ocean Code

10
Integrating Compiler Transformations
10
11
Performance of Matrix Multiply ActiveHarmony
CHiLL vs ATLAS and MKL
11
12
Must Coordinate Auto Tuners
  • Problem Warring auto tuning systems
  • Multiple components auto tuning at once
  • Tuning based on multiple changes at once
  • Solution
  • Need some level of coordination
  • Possible Answer
  • Exposing different tuning systems
  • Part of PERI Auto-tuning Effort

13
Conclusion
  • Active Harmony
  • An infrastructure for runtime tuning
  • Automatic tuning and environment adaptation
  • It works !
  • Auto Tuning Integration
  • Need to integrate multiple tools
  • Compilers, runtime, application

14
Acknowledgements
  • Coding and Experiments
  • I-Hsin Chung (IBM Watson)
  • Vahid Tabatabaee
  • Ananta Tiwari
  • Chill Integration Effort
  • Marry Hall (Utah)
  • Chun Chen (USC/ISI)
  • Jacqueline Chame (USC/ISI)
  • Funding
  • DOE PERC/PERI
  • NSF
  • LTS (DoD)
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