Design space exploration of FPGA-based Deep Convolutional Neural Networks

• Published in: Proceedings of the ASP-DAC ... Asia and South Pacific Design Automation Conference pp. 575 - 580
• Main Authors: Motamedi, Mohammad, Gysel, Philipp, Akella, Venkatesh, Ghiasi, Soheil
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.01.2016
• Subjects: Accelerators; Computer architecture; Computer simulation; Convolution; Design analysis; Design engineering; Field programmable gate arrays; Kernel; Mathematical model; Mathematical models; Neural networks; Parallel processing; Platforms; Space exploration

Deep Convolutional Neural Networks (DCNN) have proven to be very effective in many pattern recognition applications, such as image classification and speech recognition. Due to their computational complexity, DCNNs demand implementations that utilize custom hardware accelerators to meet performance...