A comparative study of shared memory parallelism on regular and irregular data structures using OpenMP and Galois

Pothukuchi, Sweta Yamini

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https://hdl.handle.net/2142/88935 Copy

Description

Title

A comparative study of shared memory parallelism on regular and irregular data structures using OpenMP and Galois

Author(s)

Pothukuchi, Sweta Yamini

Issue Date

2015-08-19

Director of Research (if dissertation) or Advisor (if thesis)

Padua, David

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• parallel
• OpenMP
• Galois

Abstract

Task and/or data parallelism can be exploited in most applications on today's multi-core processors. However, inefficient data organization, data dependencies, and hardware constraints limit scalable parallelization of these applications. In this thesis, performance and the impact of some optimizations is compared and evaluated for simple tasks using two parallel frameworks, OpenMP and Galois. Additionally, their performance on three real life applications, High Accuracy Relativistic Magnetohydrodynamics (HARM) which operates on a grid data structure; Delaunay Triangulation, which refines a triangulated mesh; and Dynamic Fracture Propagation, which operates on a triangulated mesh with adaptive refinement; is evaluated. It is found that OpenMP is a simple yet powerful tool for parallelization of most regular applications and workloads. Galois, which is specially designed for irregular data patterns, performs well for graph like structures. However, neither of them are well suited for all tasks and other frameworks must be explored to find one that is simple to use and yet powerful for all possible applications.

Graduation Semester

2015-12

Type of Resource

text

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http://hdl.handle.net/2142/88935

Copyright and License Information

Copyright 2015 Sweta Yamini Pothukuchi

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