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Distributed event-based computing

Distributed event-based computing
Distributed event-based computing
As computing systems get larger in capability - a good thing - they also
get larger in ways less desirable: cost, volume, power requirements and so on.
Further, as the datastructures necessary to support large computations grow
physically, the proportion of wallclock time spent communicating increases
dramatically at the expense of the time spent calculating. This state of affairs is
currently unacceptable and will only get worse as exa-scale machines move from
the esoteric to the commonplace. As the unit cost of non-trivial cores continues tof all, one powerful approach is to build systems that have immense numbers of
relatively small cores embedded (both geometrically and topologically) in a vast
distributed network of stored state data: take the compute to the data, rather than the other way round. In this paper, we describe POETS - Partially Ordered Event Triggered Systems. This is a novel kind of computing architecture, built upon the neuromorphic concept that has inspired such machines as SpiNNaker[1,2] and BrainScaleS[3]. The central idea is that a problem is broken down into a large set of interacting devices, which communicate asynchronously via small, hardware brokered packets (the arrival of which is an event). The set of devices is the task graph. You cannot take a conventional codebase and port it to a POETS architecture; it is necessary to strip the application back to the underlying mathematics and reconstruct the algorithm in a manner sympathetic to the solution capabilities of the machine. However, for the class of problems for which thisapproach is suitable, POETS has already demonstrated solution speedups of afactor of 200 over conventional techniques.
0927-5452
IOS Press
Brown, Andrew
5c19e523-65ec-499b-9e7c-91522017d7e0
Thomas, David
54ebbdb1-9299-4907-b574-4f2d42886832
Reeve, Jeffrey
dd909010-7d44-44ea-83fe-a09e4d492618
Tarawneh, Ghaith
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De Gennaro, Alessandro
8c78f093-4a6b-4e21-90cc-fb90e4a1c8b3
Mokhov, andrey
7ad0909b-34e8-4f32-908c-b6406b397776
Naylor, Matthew
7f0b28f7-b50f-40cc-b3ed-3821e5ef1230
Kazmierski, Tomasz
a97d7958-40c3-413f-924d-84545216092a
Brown, Andrew
5c19e523-65ec-499b-9e7c-91522017d7e0
Thomas, David
54ebbdb1-9299-4907-b574-4f2d42886832
Reeve, Jeffrey
dd909010-7d44-44ea-83fe-a09e4d492618
Tarawneh, Ghaith
1b90fbe9-1337-4216-83ba-b01115bf4000
De Gennaro, Alessandro
8c78f093-4a6b-4e21-90cc-fb90e4a1c8b3
Mokhov, andrey
7ad0909b-34e8-4f32-908c-b6406b397776
Naylor, Matthew
7f0b28f7-b50f-40cc-b3ed-3821e5ef1230
Kazmierski, Tomasz
a97d7958-40c3-413f-924d-84545216092a

Brown, Andrew, Thomas, David, Reeve, Jeffrey, Tarawneh, Ghaith, De Gennaro, Alessandro, Mokhov, andrey, Naylor, Matthew and Kazmierski, Tomasz (2018) Distributed event-based computing. In Proceedings of ParCo 2017: Parallel Computing is Everywhere. vol. 32, IOS Press. 10 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

As computing systems get larger in capability - a good thing - they also
get larger in ways less desirable: cost, volume, power requirements and so on.
Further, as the datastructures necessary to support large computations grow
physically, the proportion of wallclock time spent communicating increases
dramatically at the expense of the time spent calculating. This state of affairs is
currently unacceptable and will only get worse as exa-scale machines move from
the esoteric to the commonplace. As the unit cost of non-trivial cores continues tof all, one powerful approach is to build systems that have immense numbers of
relatively small cores embedded (both geometrically and topologically) in a vast
distributed network of stored state data: take the compute to the data, rather than the other way round. In this paper, we describe POETS - Partially Ordered Event Triggered Systems. This is a novel kind of computing architecture, built upon the neuromorphic concept that has inspired such machines as SpiNNaker[1,2] and BrainScaleS[3]. The central idea is that a problem is broken down into a large set of interacting devices, which communicate asynchronously via small, hardware brokered packets (the arrival of which is an event). The set of devices is the task graph. You cannot take a conventional codebase and port it to a POETS architecture; it is necessary to strip the application back to the underlying mathematics and reconstruct the algorithm in a manner sympathetic to the solution capabilities of the machine. However, for the class of problems for which thisapproach is suitable, POETS has already demonstrated solution speedups of afactor of 200 over conventional techniques.

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Distributed event-based computing - Accepted Manuscript
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More information

Accepted/In Press date: 14 August 2017
e-pub ahead of print date: 1 March 2018
Published date: 1 March 2018
Additional Information: This paper will be published in the conf proceedings, they have not been published yet.
Venue - Dates: ParCo, Bolonga, Italy, 2017-09-12 - 2017-09-15

Identifiers

Local EPrints ID: 418177
URI: https://eprints.soton.ac.uk/id/eprint/418177
ISSN: 0927-5452
PURE UUID: 9fd04853-753c-4ede-8e9c-9091744affe5

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Date deposited: 23 Feb 2018 17:30
Last modified: 04 Dec 2019 17:30

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Contributors

Author: Andrew Brown
Author: David Thomas
Author: Jeffrey Reeve
Author: Ghaith Tarawneh
Author: Alessandro De Gennaro
Author: andrey Mokhov
Author: Matthew Naylor
Author: Tomasz Kazmierski

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