1. Performance Technology for Scalable Parallel Systems
Allen D. Malony
Department of Computer and Information Science
University of Oregon

2. Performance Technology
Tools for performance problem solving
Empirical-based performance optimization process
Performance technology concerns
Data mining
Models
Expert systems
Performance Technology
Performance Tuning
Experiment management
Performance storage
Performance Technology
hypotheses
Performance
Diagnosis
properties
Instrumentation
Measurement
Analysis
Visualization
Performance Technology
Performance
Experimentation
characterization
Performance
Observation

3. TAU Parallel Performance System Project
Tuning and Analysis Utilities (15+ year project effort)
Performance system framework for HPC systems
Integrated, scalable, and flexible
Target parallel programming paradigms
Integrated toolkit for performance problem solving
Instrumentation, measurement, analysis, and visualization
Portable performance profiling and tracing facility
Performance data management and data mining
Partners
LLNL, ANL, LANL
Research Centre Jülich, TU Dresden

4. TAU Parallel Performance System Goals
Portable (open source) parallel performance system
Computer system architectures and operating systems
Different programming languages and compilers
Multi-level, multi-language performance instrumentation
Flexible and configurable performance measurement
Support for multiple parallel programming paradigms
Multi-threading, message passing, mixed-mode, hybrid, object oriented, component-based
Support for performance mapping
Integration of leading performance technology
Scalable (very large) parallel performance analysis

5. TAU Performance System Components
TAU Architecture
Program Analysis
Performance Data Mining
PDT
PerfExplorer
Parallel Profile Analysis
PerfDMF
Performance Monitoring
ParaProf
TAUoverSupermon

6. TAU Instrumentation and Measurement

7. TAU Analysis

8. TAU on HPC Platforms with Intel Processors
ARL (JVN / MJM, x86_64 Linux NetworX)
14.7 TF / 52.8 TF, 2048 / 4400 processors
ARFL (Hawk, Eagle ia64 SGI Altix)
59 TF, 9216 processors
NCSA (Abe, x86_64 Dell)
89.47 TF, 9600 cores
NASA (Columbia, ia64 SGI Altix)
60.96 TF, processors
MHPCC (Jaws, x86_64 Dell)
60 TF, 5120 processors
TACC (Lonestar, x86_64 Dell)
62 TF, 5840 processors

9. TAU on Leadership Class Facilities and TeraGrid
Argonne National Laboratory
IBM BG/P
111 TF
32768 processors
Oak Ridge National Laboratory
Cray XT-4
119 TF peak
23416 cores (AMD Opteron)
Texas Advanced Computing Center
Sun Blade 8000
504 TF peak
62976 cores (AMD Opteron)

10. Recent Funding
A. Malony, S. Shende, N. Nystrom, S. Moore, R. Kufrin, SDCI HPC Improvement: High-Productivity Performance Engineering (Tools, Methods, Training) for NSF HPC Applications, NSF Software Development for Cyberinfrastructure (SDCI), 11/1/ /31/2010.
A. Malony, S. Shende, Knowledge-based Parallel Performance Technology, DOE Office of Science, 9/1/2007-8/31/2010.
P. Beckman, A. Malony, Extreme Performance Scalable Operating Systems, DOE Office of Science, 12/1/04-1/31/08.
A. Malony, S. Shende, Application-Specific Performance Technology for Productive Parallel Computing, DOE Office of Science, 5/1/05-4/30/08.
S. McKee, A. Malony, G. Tyson, ST-HEC: Collaborative Research: Scalable, Interoperable Tools to Support Autonomic Optimization of High-End Applications, NSF High-End Computing (HEC), 11/1/04-10/31/07.
A. Malony, Multi-core Parallel Programming and Performance Tools, Intel equipment grant, 9/15/2006.
A. Malony, M. Sottile, Multi-core Parallel Programming, Intel equipment grant, 11/1/2007.

11. Intel Contacts Justin Rattner, Intel Senior Fellow, Vice-President
Director, Corporate Technology Group
In 1988 Rattner (at Intel Scientific Computers) suggested implementing a performance monitor for the iPSC/2 hypercube
A. Malony, D. Reed, “A Hardware- Based Performance Monitor for the Intel iPSC/2 Hypercube,” ICS 1990.
David Kuck, Intel Fellow
Software and Solutions Group
Director, Parallel and Distributed Solutions Division
Worked for Kuck at the Center for Supercomputing Research and Development, University of Illinois, Urbana-Champaign
Tim Mattson, Senior Research Scientist
Computational Software Laboratory
Werner Krotz-Vogel
Technical Marketing Engineer, Intel Cluster Tools

12. Support Acknowledgements
Department of Energy (DOE)
Office of Science
ASCR, Argonne National Lab
ASC/NNSA
University of Utah ASC/NNSA Level 1
ASC/NNSA, Lawrence Livermore National Lab
Department of Defense (DoD)
HPC Modernization Office (HPCMO)
NSF Software Development for Cyberinfrastructure
Los Alamos National Laboratory
Research Centre Juelich, TU Dresden
ParaTools, Inc.