Theses and Dissertations

ORCID

https://orcid.org/0009-0000-0040-7220

Advisor

Khan, Samee

Committee Member

Koshka, Yaroslav

Committee Member

Jones, Bryan

Date of Degree

5-10-2024

Original embargo terms

Immediate Worldwide Access

Document Type

Graduate Thesis - Open Access

Major

Electrical and Computer Engineering

Degree Name

Master of Science (M.S.)

College

James Worth Bagley College of Engineering

Department

Department of Electrical and Computer Engineering

Abstract

Heterogeneous computing (HC) systems are essential parts of modern-day computing architectures such as cloud, cluster, grid, and edge computing. Many algorithms exist within the classical environment for mapping computational tasks to the HC system’s nodes, but this problem is not well explored in the quantum area. In this work, the practicality, accuracy, and computation time of quantum mapping algorithms are compared against eleven classical mapping algorithms. The classical algorithms used for comparison include A-star (A*), Genetic Algorithm (GA), Simulated Annealing (SA), Genetic Simulated Annealing (GSA), Opportunistic Load Balancing (OLB), Minimum Completion Time (MCT), Minimum Execution Time (MET), Tabu, Min-min, Max-min, and Duplex. These algorithms are benchmarked using several different test cases to account for varying system parameters and task characteristics. This study reveals that a quantum mapping algorithm is feasible and can produce results similar to classical algorithms.

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