Mohsen Koohi EsfahaniSupervisors: Hans Vandierendonck and Peter Kilpatrick Thesis in PDF formatThesis on QUB Pure Portal Graph algorithms find several usages in industry, science, humanities, and technology. The fast-growing size of graph datasets in the context of the processing model of the current hardware has resulted in different bottlenecks such […]
graph traversal
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36th ACM International Conference on Supercomputing 2022June 27-30, 2022Acceptance Rate: 25% DOI: 10.1145/3524059.3532365Authors’ Copy (PDF Format) The Minimum Spanning Forest (MSF) problem finds usage in many different applications. While theoretical analysis shows that linear-time solutions exist, in practice, parallel MSF algorithms remain computationally demanding due to the continuously increasing size […]
DOI: 10.1145/3524059.3532360 This paper proposes software-defined floating-point number formats for graph processing workloads, which can improve performance in irregular workloads by reducing cache misses. Efficient arithmetic on software-defined number formats is challenging, even when based on conversion to wider, hardware-supported formats. We derive efficient conversion schemes that are tuned to […]
2021 IEEE International Symposium on Workload Characterization (IISWC’21)November 7-9, 2021Acceptance Rate: 39.5%DOI: 10.1109/IISWC53511.2021.00020 Authors’ Copy (PDF Format) Graph reordering algorithms try to improve locality of graph algorithms by assigning new IDs to vertices that ultimately changes the order of random memory accesses. While graph relabeling algorithms such as SlashBurn, GOrder, […]
50th International Conference on Parallel Processing (ICPP’21)August 9-12, 2021Acceptance Rate: 26.4% DOI:10.1145/3472456.3472462ACM Digital LibraryPDF Version (Authors’ Copy) This paper investigates the implications made by the structure of real-world graphs with power-law degree distribution on the locality of SpMV graph analytics, and by considering the efficacy of locality optimizing graph reordering […]
Relabeling (reordering) algorithms aim to improve the poor memory locality of graph processing by changing the order of vertices. This paper analyses the functionality of three state-of-the-art relabeling algorithms: SlashBurn, GOrder, and Rabbit-Order for real-world graphs. We use a number of techniques to explain how locality is affected by relabeling algorithms and how locality of different datasets (like social networks, web graphs) is enhanced by relabeling algorithms. This paper also investigates why different push and pull traversal of different datasets show different behaviours by introducing push locality and pull locality.
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, […]