Talk :A Peripheral Circuit Reuse Structure Integrated with a Retimed Data Flow for Low Power RRAM Crossbar-based CNN

报告时间：2018年7月5号，9:30am-11:30am

报告地点：数计学院4号楼第2报告厅

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.

Speaker Bio:

邱柯妮博士于香港城市大学获得计算机科学博士学位，目前为首都师范大学信息工程学院教授。邱教授的研究方向包括计算机及嵌入式系统体系结构、非易失存储器体系结构，尤其关注系统的软硬件协同设计对计算和存储的性能、功耗及可靠性的影响。她以第一作者在TC、TCAD、DAC、DATE、ICCD等计算机体系结构和EDA设计领域国际知名期刊和会议上发表了多篇高水平学术论文，荣获ICCD’16、 ICESS’17最佳论文奖、ISLPED’17的设计竞赛决赛奖以及清华-罗姆论坛TRIFIA'18最佳海报奖’。