Date of Award
Summer 8-2020
Degree Type
Thesis-Restricted
Degree Name
M.S.
Degree Program
Computer Science
Department
Computer Science
Major Professor
Dr. Shaikh M Arifuzzaman
Second Advisor
Dr. Minhaz Zibran
Third Advisor
Dr. Tamjidul Hoque
Abstract
An algorithm designer working with parallel computing systems should know how the characteristics of their implemented algorithm affects various performance aspects of their parallel program. It would be beneficial to these designers if each algorithm came with a specific set of standards that identified which algorithms worked better for a specified system. Therefore, the goal of this paper is to take implementations of four graphing algorithms, extract their features such as memory consumption, scalability using profilers (Vtunes /Tau) to determine which algorithms work to their fullest potential in one of the three systems: GPU, shared memory system, or distributed memory system. The features extracted in this study were scalability, speedup, and parallel efficiency. We find that when looking at various parallel algorithms: Community Detection, Communities through Directed Affiliations (Coda), BigClam, and Breadth First Search all achieved noticeable speedup with increasing number of cores.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Nachuma, Costain, "Using High-Performance Computing Profilers to Understand the Performance of Graph Algorithms" (2020). University of New Orleans Theses and Dissertations. 2797.
https://scholarworks.uno.edu/td/2797
Thesis Draft
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Systems Architecture Commons
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.