Paradigms and strategies for scientific computing on distributed memory concurrent computers

• Main Authors: Foster, I. T., Walker, D. W.
• Other Authors: United States. Department of Energy., National Science Foundation (U.S.)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Argonne National Laboratory 1994
• Subjects: 99 General And Miscellaneous//Mathematics; Computing; And Information Science; Computerized Simulation; Programming; Mathematics And Computers; Parallel Processing; Computer Networks 990200; Distributed Data Processing; Array Processors; Fortran; Orca
• Online Access: https://digital.library.unt.edu/ark:/67531/metadc1386797/

In this work we examine recent advances in parallel languages and abstractions that have the potential for improving the programmability and maintainability of large-scale, parallel, scientific applications running on high performance architectures and networks. This paper focuses on Fortran M, a set of extensions to Fortran 77 that supports the modular design of message-passing programs. We describe the Fortran M implementation of a particle-in-cell (PIC) plasma simulation application, and discuss issues in the optimization of the code. The use of two other methodologies for parallelizing the PIC application are considered. The first is based on the shared object abstraction as embodied in the Orca language. The second approach is the Split-C language. In Fortran M, Orca, and Split-C the ability of the programmer to control the granularity of communication is important is designing an efficient implementation.