A framework for accelerating neuromorphic-vision algorithms on FPGAs

M. Debole; A. Al Maashri; M. Cotter; C. L. Yu; Chaitali Chakrabarti; V. Narayanan

doi:10.1109/ICCAD.2011.6105351

A framework for accelerating neuromorphic-vision algorithms on FPGAs

M. Debole, A. Al Maashri, M. Cotter, C. L. Yu, Chaitali Chakrabarti, V. Narayanan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Implementations of neuromorphic algorithms are traditionally implemented on platforms which consume significant power, falling short of their biologically underpinnings. Recent improvements in FPGA technology have led to FPGAs becoming a platform in which these rapidly evolving algorithms can be implemented. Unfortunately, implementing designs on FPGAs still prove challenging for nonexperts, limiting their use in the neuroscience domain. In this paper, a FPGA framework is presented which enables neuroscientists to compose multi-FPGA systems for a cortical object classification model. This is demonstrated by mapping this algorithm onto two distinct platforms providing speedups of up to 28X over a reference CPU implementation.

Original language	English (US)
Title of host publication	2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011
Pages	810-813
Number of pages	4
DOIs	https://doi.org/10.1109/ICCAD.2011.6105351
State	Published - Dec 1 2011
Event	2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011 - San Jose, CA, United States Duration: Nov 7 2011 → Nov 10 2011

Publication series

Name	IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
ISSN (Print)	1092-3152

Other

Other	2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011
Country/Territory	United States
City	San Jose, CA
Period	11/7/11 → 11/10/11

Keywords

FPGA application mapping
FPGA programming
Multi-FPGA partitioning
Neuromorphic vision algorithms

ASJC Scopus subject areas

Software
Computer Science Applications
Computer Graphics and Computer-Aided Design

Access to Document

10.1109/ICCAD.2011.6105351

Cite this

Debole, M., Maashri, A. A., Cotter, M., Yu, C. L., Chakrabarti, C., & Narayanan, V. (2011). A framework for accelerating neuromorphic-vision algorithms on FPGAs. In 2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011 (pp. 810-813). Article 6105351 (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD). https://doi.org/10.1109/ICCAD.2011.6105351

A framework for accelerating neuromorphic-vision algorithms on FPGAs. / Debole, M.; Maashri, A. Al; Cotter, M. et al.
2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011. 2011. p. 810-813 6105351 (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Debole, M, Maashri, AA, Cotter, M, Yu, CL, Chakrabarti, C & Narayanan, V 2011, A framework for accelerating neuromorphic-vision algorithms on FPGAs. in 2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011., 6105351, IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, pp. 810-813, 2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011, San Jose, CA, United States, 11/7/11. https://doi.org/10.1109/ICCAD.2011.6105351

Debole M, Maashri AA, Cotter M, Yu CL, Chakrabarti C, Narayanan V. A framework for accelerating neuromorphic-vision algorithms on FPGAs. In 2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011. 2011. p. 810-813. 6105351. (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD). doi: 10.1109/ICCAD.2011.6105351

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A framework for accelerating neuromorphic-vision algorithms on FPGAs

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Keywords

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