NDLI: Merging the interface: power, area and accuracy co-optimization for RRAM crossbar-based mixed-signal computing system

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Merging the interface: power, area and accuracy co-optimization for RRAM crossbar-based mixed-signal computing system

Content Provider	ACM Digital Library
Author	Yang, Huazhong Xia, Lixue Li, Boxun Wang, Yu Gu, Peng
Abstract	The invention of resistive-switching random access memory (RRAM) devices and RRAM crossbar-based computing system (RCS) demonstrate a promising solution for better performance and power efficiency. The interfaces between analog and digital units, especially AD/DAs, take up most of the area and power consumption of RCS and are always the bottleneck of mixed-signal computing systems. In this work, we propose a novel architecture, MEI, to minimize the overhead of AD/DA by MErging the Interface into the RRAM crossbar. An optional ensemble method, the Serial Array Adaptive Boosting (SAAB), is also introduced to take advantage of the area and power saved by MEI and boost the accuracy and robustness of RCS. On top of these two methods, a design space exploration is proposed to achieve trade-offs among accuracy, area, and power consumption. Experimental results on 6 diverse benchmarks demonstrate that, compared with the traditional architecture with AD/DAs, MEI is able to save 54.63%~86.14% area and reduce 61.82%~86.80% power consumption under quality guarantees; and SAAB can further improve the accuracy by 5.76% on average and ensure the system performance under noisy conditions.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781450335201
DOI	10.1145/2744769.2744870
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-06-07
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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