Affiliation:
1. Wuhan National Laboratory for Optoelectronics, Key Laboratory of Information Storage System (School of Computer Science and Technology, Huazhong University of Science and Technology), Ministry of Education of China
Abstract
Emerging Resistive Random Access Memory (ReRAM) is a promising candidate as the replacement for DRAM due to its low standby power, high density, high scalability, and nonvolatility. By employing the unique crossbar structure, ReRAM can be constructed with extremely high density. However, the crossbar ReRAM faces some serious challenges in terms of performance, reliability, and energy consumption. First, ReRAM’s crossbar structure causes an IR drop problem due to wire resistance and sneak currents, which results in nonuniform access latency in ReRAM banks and reduces its reliability. Second, without access transistors in the crossbar structure, write disturbance results in serious data reliability problem. Third, the access latency, reliability, and energy use of ReRAM arrays are significantly influenced by the data patterns involved in a write operation.
To overcome the challenges of the crossbar ReRAM, we propose a novel circuit architecture co-optimization framework for improving the performance, reliability, and energy use of ReRAM-based main memory system, called CACF. The proposed CACF consists of three levels, including the circuit level, circuit architecture level, and architecture level. At the circuit level, to reduce the IR drops along bitlines, we propose a double-sided write driver design by applying write drivers along both sides of bitlines and selectively activating the write drivers. At the circuit architecture level, to address the write disturbance with low overheads, we propose a RESET disturbance detection scheme by adding disturbance reference cells and conditionally performing refresh operations. At the architecture level, a region partition with address remapping method is proposed to leverage the nonuniform access latency in ReRAM banks, and two flip schemes are proposed in different regions to optimize the data patterns involved in a write operation. The experimental results show that CACF improves system performance by 26.1%, decreases memory access latency by 22.4%, shortens running time by 20.1%, and reduces energy consumption by 21.6% on average over an aggressive baseline. Meanwhile, CACF significantly improves the reliability of ReRAM-based memory systems.
Funder
Ministry of Education, China
State Key Laboratory of Computer Architecture
Engineering Research Center of Data Storage Systems and Technology
National High Technology Research and Development Program
National Natural Science Foundation of China
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Information Systems,Software
Cited by
27 articles.
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