Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79428
Title: A peripheral circuit reuse structure integrated with a retimed data flow for low power RRAM crossbar-based CNN
Authors: Qiu, K
Chen, W
Xu, Y
Xia, L
Wang, Y
Shao, Z 
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Proceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018, 2018, v. 2018-January, p. 1057-1062 How to cite?
Abstract: Convolutional computations implemented in RRAM crossbar-based Computing System (RCS) demonstrate the outstanding advantages of high performance and low power. However, current designs are energy-unbalanced among the three parts of RRAM crossbar computation, peripheral circuits and memory accesses, and the latter two factors can significantly limit the potential gains of RCS. Addressing the problem of high power overhead of peripheral circuits in RCS, this paper proposes a Peripheral Circuit Unit (PeriCU)-Reuse scheme to meet power budgets in energy constrained embedded systems. The underlying idea is to put the expensive ADCs/DACs onto spotlight and arrange multiple convolution layers to be sequentially served by the same PeriCU. In the solution, the first step is to determine the number of PeriCUs which are organized by cycle frames. Inside a cycle frame, the layers are computed in parallel inter-PeriCUs while sequentially intra-PeriCU. Furthermore, a layer retiming technique is exploited to further improve the energy of RCS by assigning two adjacent layers within the same PeriCU so as to bypass the energy consuming memory accesses. The experiments of five convolutional applications validate that the PeriCU-Reuse scheme integrated with the retiming technique can efficiently meet variable power budgets, and further reduce energy consumption efficiently.
Description: 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018, Dresden, Germany, 19-23 March 2018
URI: http://hdl.handle.net/10397/79428
ISBN: 9783981926316
DOI: 10.23919/DATE.2018.8342168
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