Object-Oriented Support for Adaptive Methods on Paranel Machines

Issue title: The First Annual Object-Oriented Numerics Conference (OON-SKI '93)

Article type: Research Article

Authors: BHATT, SANDEEP | CHEN, MARINA | COWIE, JAMES | LIN, CHENG-YEE | LIU, PANGFENG

Affiliations: Bell Communications Research, Morristown, NJ 07962 | Department of Computer Science, Yale University, New Haven, CT 06520

Abstract: This article reports on experiments from our ongoing project whose goal is to develop a C++ library which supports adaptive and irregular data structures on distributed memory supercomputers. We demonstrate the use of our abstractions in implementing "tree codes" for large-scale N-body simulations. These algorithms require dynamically evolving treelike data structures, as well as load-balancing, both of which are widely believed to make the application difficult and cumbersome to program for distributed-memory machines. The ease of writing the application code on top of our C++ library abstractions (which themselves are application independent), and the low overhead of the resulting C++ code (over hand-crafted C code) supports our belief that object-oriented approaches are eminently suited to programming distributed-memory machines in a manner that (to the applications programmer) is architecture-independent. Our contribution in parallel programming methodology is to identify and encapsulate general classes of communication and load-balancing strategies useful across applications and MIMD architectures. This article reports experimental results from simulations of half a million particles using multiple methods.

Journal: Scientific Programming, vol. 2, no. 4, pp. 179-192, 1993