Biologically-Inspired Massively Parallel Architectures - computing beyond a million processors

Lead Research Organisation: University of Cambridge
Department Name: Computer Science and Technology

Abstract

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Publications

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Audzevich Y (2014) Power Optimized Transceivers for Future Switched Networks in IEEE Transactions on Very Large Scale Integration (VLSI) Systems

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Banerjee A (2009) An Energy and Performance Exploration of Network-on-Chip Architectures in IEEE Transactions on Very Large Scale Integration (VLSI) Systems

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Brown A (2012) Behavioural synthesis utilising recursive definitions in IET Computers & Digital Techniques

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D Greenfield (2009) Implications of Electronics Technology Trends to Algorithm Design in The Computer Journal

 
Description There were many findings including:

* Award winning work on "Communication Locality in Computation: Software, Chip Multiprocessors and Brains" that won the UK Distinguished dissertation prize.
* Implications of Electronics Technology Trends to Algorithm Design
* Interconnect for commodity FPGA clusters: standardized or customized?
* Reliably Prototyping Large SoCs Using FPGA Clusters
* Managing the FPGA Memory Wall: custom computing or vector processing?
* Bluehive - A Field-Programmable Custom Computing Machine for Extreme-Scale Real-Time Neural Network Simulation
* Rapid codesign of a soft vector processor and its compiler
Exploitation Route The papers produced on this project already have hundreds of citations, so we definitely influenced related research.
Sectors Digital/Communication/Information Technologies (including Software)

URL http://www.cl.cam.ac.uk/research/comparch/research/bimpa.html
 
Description Programme Grant
Amount £4,981,302 (GBP)
Funding ID EP/N031768/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 04/2016 
End 11/2021
 
Description BIMPA partners 
Organisation University of Manchester
Department Materials Performance Centre
Country United Kingdom 
Sector Academic/University 
PI Contribution Massively parallel computer architecture for neuronal systems
Collaborator Contribution Extensive collaboration on computer architectures and algorithms to describe massively parallel neuronal systems.
Impact Research papers.
Start Year 2009
 
Description BIMPA partners 
Organisation University of Sheffield
Country United Kingdom 
Sector Academic/University 
PI Contribution Massively parallel computer architecture for neuronal systems
Collaborator Contribution Extensive collaboration on computer architectures and algorithms to describe massively parallel neuronal systems.
Impact Research papers.
Start Year 2009
 
Description BIMPA partners 
Organisation University of Southampton
Department School of Electronics and Computer Science Southampton
Country United Kingdom 
Sector Academic/University 
PI Contribution Massively parallel computer architecture for neuronal systems
Collaborator Contribution Extensive collaboration on computer architectures and algorithms to describe massively parallel neuronal systems.
Impact Research papers.
Start Year 2009