A framework for accelerating neuromorphic-vision algorithms on FPGAs

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

*المؤلف المقابل لهذا العمل

نتاج البحث

7 اقتباسات (Scopus)

ملخص

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.

اللغة الأصليةEnglish
عنوان منشور المضيف2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011
الصفحات810-813
عدد الصفحات4
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2011
منشور خارجيًانعم
الحدث2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011 - San Jose, CA
المدة: نوفمبر ٧ ٢٠١١نوفمبر ١٠ ٢٠١١

سلسلة المنشورات

الاسمIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
رقم المعيار الدولي للدوريات (المطبوع)1092-3152

Other

Other2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011
الدولة/الإقليمUnited States
المدينةSan Jose, CA
المدة١١/٧/١١١١/١٠/١١

ASJC Scopus subject areas

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