FPGA-accelerator system for computing biologically inspired feature extraction models

Michael DeBole*, Yang Xiao, Chi Li Yu, Ahmed Al Maashri, Matthew Cotter, Chaitali Chakrabarti, Vijaykrishnan Narayanan

*المؤلف المقابل لهذا العمل

نتاج البحث

3 اقتباسات (Scopus)

ملخص

Neuromorphic algorithms for computer-based vision may be the next step towards improving the way computers gather and interpret visual information. However, these algorithms typically have high computational demands making them difficult to deploy in embedded environments where power consumption is equally as important as performance. In this paper, we present an embedded implementation of a ventral visual pathway model, HMAX. We describe an embedded FPGA system that implements the model, as well as accelerator engines necessary to ensure adequate performance. The final system is shown to operate within a power budget of 3W while achieving up to 16.5X speedup over a pure embedded processor implementation.

اللغة الأصليةEnglish
عنوان منشور المضيفConference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
الصفحات751-755
عدد الصفحات5
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2011
منشور خارجيًانعم
الحدث45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 - Pacific Grove, CA
المدة: نوفمبر ٦ ٢٠١١نوفمبر ٩ ٢٠١١

سلسلة المنشورات

الاسمConference Record - Asilomar Conference on Signals, Systems and Computers
رقم المعيار الدولي للدوريات (المطبوع)1058-6393

Other

Other45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
الدولة/الإقليمUnited States
المدينةPacific Grove, CA
المدة١١/٦/١١١١/٩/١١

ASJC Scopus subject areas

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