Multicore programming in pMatlab using distributed arrays

ABSTRACT

Matlab is one of the most commonly used languages for scientific computing with approximately one million users worldwide. Many of the programs written in matlab can benefit from the increased performance offered by multicore processors and parallel computing clusters. The Lincoln pMatlab library (http://www.ll.mit.edu/pMatlab) allows high performance parallel programs to be written quickly using the distributed arrays programming paradigm. This talk provides an introduction to distributed arrays programming and will describe the best programming practices for using distributed arrays to produce programs that perform well on multicore processors and parallel computing clusters. These practices include understanding the concepts of parallel concurrency vs. parallel data locality, using Amdahl's Law, and a well defined design-code-debug-test process for parallel codes.

INDEX TERMS

Primary Classification:
  D. Software
  D.1 PROGRAMMING TECHNIQUES
      D.1.3 Concurrent Programming
          Subjects: Parallel programming

Additional Classification:
  E. Data
  E.1 DATA STRUCTURES
      Subjects: Distributed data structures

General Terms:
Design

Keywords:
distributed arrays, parallel computing