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Implementation of Graph Kernels on Multi core Architecture


Abstract Graphs are one of the key data structures for many real-world computing applica-

tions such as machine learning, social networks, genomics etc. The main challenges of

graph processing include diculty in parallelizing the workload that results in work-

load imbalance, poor memory locality and very large number of memory accesses.

This causes large-scale graph processing to be very expensive.

This thesis presents implementation of a select set of graph kernels on a multi-core

architecture, Transmuter. The kernels are Breadth-First Search (BFS), Page Rank

(PR), and Single Source Shortest Path (SSSP). Transmuter is a multi-tiled architec-

ture with 4 tiles and 16 general processing elements (GPE) per tile that supports a

two level cach... (more)
Created Date 2019
Contributor RENGANATHAN, SRINIDHI (Author) / CHAKRABARTI, CHAITALI (Advisor) / Shrivastava, Aviral (Committee member) / Mudge, Trevor (Committee member) / Arizona State University (Publisher)
Subject Engineering
Type Masters Thesis
Extent 51 pages
Language English
Copyright
Note Masters Thesis Electrical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis