Principal Investigators:

Jim Browne - University of Texas at Austin
Vikram Adve - Rice University
Rajive Bagrodia - University of California at Los Angeles
Elias Houstis - Purdue University
Olaf Lubeck - Los Alamos National Laboratory
Pat Teller - University of Texas at El Paso
Mary Vernon - University of Wisconsin-Madison

The POEMS project will create and demonstrate a capability for prediction of the end-to-end performance of parallel/distributed implementations of large scale adaptive applications. POEMS modeling capability will span applications, operating systems including parallel I/O, and architecture. Effort will focus on the areas where there is little convention wisdom such execution behaviors of adaptive algorithms on multi-level memory hierarchies and parallel I/O operations.

POEMS will provide:

  • A language for composing models from component models
  • Derivation of models of applications as data flow graphs from HPF programs,
  • A library of component models spanning from workloads to memory hierarchies and at levels of resolution ranging large grain data flow graphs to instruction streams and from probabilistic to fully deterministic.
  • parallel execution of the models
  • a knowledge base of performance data on commonly used algorithms parameterized for architectural characteristics.

POEMS development will be driven by modeling a full-scale LANL ASCI application code executing on an ASCI architecture.

This version of POEMS focuses on high performance computational applications and architectures. But POEMS technology can be applied to other large complex dynamic computer/communication systems as as GloMo and Quorum.



Web / FTP Sites

POEMS web page was created by Margarita Faudoa-Molina

Last Modified: 16 November 1998
Shyamal Mitra