ATME: a parallel programming environment for applications with conditional task attributes

Abstract

Parallel applications with inconstant usage patterns presents a big challenge to programmers in that the spawning of tasks and the communication between them may be conditional (named "conditional parallel programming"). Ideally, the programmer should not be burdened by operational issues which have little relationship to the application itself. This paper proposes a new parallel programming environment, ATME, to automate task scheduling in conditional parallel programming. By adaptively producing accurate estimates of the task model prior to execution, ATME modifies task distribution to improve the system and application performance.