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)
|Contributor||RENGANATHAN, SRINIDHI (Author) / CHAKRABARTI, CHAITALI (Advisor) / Shrivastava, Aviral (Committee member) / Mudge, Trevor (Committee member) / Arizona State University (Publisher)|
|Note||Masters Thesis Electrical Engineering 2019|
|Collaborating Institutions||Graduate College / ASU Library|
|Additional Formats||MODS / OAI Dublin Core / RIS|