Thesis on QUB Pure PortalThesis in PDF Format Author: Jiawen Sun, https://www.linkedin.com/in/jiawen-sun-33b368103/ As shared memory systems support terabyte-sized main memory, they provide an opportunity to perform efficient graph analytics on a single machine. Graph analytics is characterised by frequent synchronisation, which is addressed in part by shared memory systems. However, […]
Graph Algorithms
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The following git repository contains source code of GraphGrind https://github.com/DIPSA-QUB/GraphGrind
https://doi.org/10.1109/ICPP.2017.27 This paper investigates how to improve the memory locality of graph-structured analytics on large-scale shared memory systems. We demonstrate that a graph partitioning where all in-edges for a vertex are placed in the same partition improves memory locality. However, realising performance improvement through such graph partitioning poses several challenges […]
On July 11th, Hans gave a talk on “GraphGrind: Taming Irregular Memory Accesses in Graph Analytics Workloads” at the UK ManyCore workshop https://manycore.org.uk/ukmac2017.html The analysis of graph-structured data is gaining importance due to its relevance to social media and big data. Due to the interconnection patterns in social network graphs, the […]
https://doi.org/10.1145/3079079.3079097 We investigate how graph partitioning adversely affects the performance of graph analytics. We demonstrate that graph partitioning induces extra work during graph traversal and that graph partitions have markedly different connectivity than the original graph. By consequence, increasing the number of partitions reaches a tipping point after which overheads […]