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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People |
ORCID iD |
| Simon Moore (Principal Investigator) | |
| Robert Mullins (Co-Investigator) |
Publications
Audzevich Y
(2014)
Power Optimized Transceivers for Future Switched Networks
in IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Banerjee A
(2009)
Flow-aware allocation for on-chip networks
Banerjee A
(2009)
An Energy and Performance Exploration of Network-on-Chip Architectures
in IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Barrow-Williams N
(2009)
A communication characterisation of Splash-2 and Parsec
Barrow-Williams N
(2010)
Proximity coherence for chip multiprocessors
Bassett DS
(2010)
Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.
in PLoS computational biology
Brown A
(2012)
Behavioural synthesis utilising recursive definitions
in IET Computers & Digital Techniques
D Greenfield
(2009)
Implications of Electronics Technology Trends to Algorithm Design
in The Computer Journal
Fensch C
(2013)
Designing a Physical Locality Aware Coherence Protocol for Chip-Multiprocessors
in IEEE Transactions on Computers
| 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 | 05/2016 |
| 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 |