Document Type

Thesis

Date of Award

12-31-2020

Degree Name

Master of Science in Computer Science - (M.S.)

Department

Computer Science

First Advisor

David A. Bader

Second Advisor

Ioannis Koutis

Third Advisor

Dimitri Theodoratos

Abstract

Finding the transitive closure of a graph is a fundamental graph problem where another graph is obtained in which an edge exists between two nodes if and only if there is a path in our graph from one node to the other. The reachability matrix of a graph is its transitive closure. This thesis describes a novel approach that uses anti-sections to obtain the transitive closure of a graph. It also examines its advantages when implemented in parallel on a CPU using the Hornet graph data structure.

Craph representations of real-world systems are typically sparse in nature due to lesser connectivity between nodes. The anti-section approach is designed specifically to improve performance for large scale sparse graphs. The NVIDIA Titan V CPU is used for the execution of the anti-section parallel implementations. The Dual-Round and Hash-Based implementations of the Anti-Section transitive closure approach provide a significant speedup over several parallel and sequential implementations.

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