Biologically-Inspired Massively Parallel Architectures - computing beyond a million processors
Lead Research Organisation:
University of Cambridge
Department Name: Computer Science and Technology
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
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
(2011)
Proximity coherence for chip-multiprocessors
Barrow-Williams N
(2010)
Proximity coherence for chip multiprocessors
Bassett D
(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
| 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 |