Scalable Concurrent Programming Project, Scalable Concurrent Programming Laboratory.

Abstract

Proposed at a time when the community was primarily concerned with statically structured problems in scientific computing, the Scalable Concurrent Programming Project was motivated by the following general perceptions: (1) For much of this century, scientific computing has been dominated by large regular problems and their associated computational techniques. This has been a direct result of relatively poor uniprocessor performance, simplistic software tools, and the associated education from previous generations; (2) Device technology is rapidly approaching the physical limits of CMOS technology. During the next decade vast improvements in uniprocessor performance will be increasingly difficult and expensive to obtain. Concurrency is the door to the future; Scalability is the key; and (3) As performance improves, we will not solve the same problems faster, but rather we will solve completely new and more realistic computational problems. These irregular problems will combine computations in structures, materials, fluids, and electromagnetics. They will be three-dimensional in nature, involve complex moving boundaries, and resolve transient effects. They will become the cornerstone of design, test, and manufacturing in a broad range of industries currently dominated by empiricism.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1996
Accession Number
ADA315138

Entities

People

  • Steven Taylor

Organizations

  • California Institute of Technology

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Compilers
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Corporations
  • Data Sets
  • Differential Equations
  • Embedded Systems
  • Equations
  • Fluid Dynamics
  • Ion Thrusters
  • Monte Carlo Method
  • Parallel Computing

Readers

  • Computational Fluid Dynamics (CFD)
  • Parallel and Distributed Computing.
  • Systems Analysis and Design