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Using neuromorphic hardware for the scalable execution of massively parallel, communication-intensive algorithms
File(s)
report_louis(1).pdf (6.56 MB)
Accepted version
Author(s)
Blin, Louis
Awan, Ahsan Javed
Heinis, Thomas
Type
Conference Paper
Abstract
Neuromorphic hardware like SpiNNaker offers massive parallelism and efficient communication of small payloads to accelerate the simulation of spiking neurons in neural networks. In this paper, we demonstrate that this hardware is also beneficial for other for applications which require massive parallelism and the large-scale exchange of small messages. More specifically, we study the scalability of PageRank on SpiNNaker and compare it to an implementation on traditional hardware. In our experiments, we show that PageRank on SpiNNaker scales better than on traditional multicore architectures.
Date Issued
2019-01-10
Date Acceptance
2018-12-17
Citation
2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion), 2019, pp.89-94
URI
URL
DOI
ISBN
9781728103594
Publisher
IEEE
Start Page
89
End Page
94
Journal / Book Title
2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)
Copyright Statement
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (E
Commission of the European Communities
Identifier
https://doi.org/10.1109/UCC-Companion.2018.00040
Grant Number
EP/N023242/1
758907 -HBP SGA2- H2020 - RIA
Source
2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)
Subjects
Science & Technology
Technology
Computer Science, Information Systems
Computer Science, Theory & Methods
Computer Science
Publication Status
Published
Start Date
2018-12-17
Finish Date
2018-12-20
Coverage Spatial
Zurich, Switzerland
Date Publish Online
2019-01-10