SMARTS: Exploiting Temporal Locality and Parallelism through Vertical Execution
In the solution of large-scale numerical prob- lems, parallel computing is becoming simultaneously more important and more difficult. The complex organization of today's multiprocessors with several memory hierarchies has forced the scientific programmer to make a choice between simple but unscalable code and scalable but extremely com- plex code that does not port to other architectures. This paper describes how the SMARTS runtime system and the POOMA C++ class library for high-performance scientific computing work together to exploit data parallelism in scientific applications while hiding the details of manag- ing parallelism and data locality from the user. We present innovative algorithms, based on the macro -dataflow model, for detecting data parallelism and efficiently executing data- parallel statements on shared-memory multiprocessors. We also desclibe how these algorithms can be implemented on clusters of SMPS.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- W-7405-ENG-36
- OSTI ID:
- 7401
- Report Number(s):
- LA-UR-99-16; ON: DE00007401
- Resource Relation:
- Conference: International Conference Supercomputing (ICS99), Rhodes, Greece, June 20-25, 1999
- Country of Publication:
- United States
- Language:
- English
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