Description

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

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

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Date Created
  • 2019
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  • Text
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    • Masters Thesis Electrical Engineering 2019

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