摘要
As the scaling of applications increases, the demand of main memory capacity increases in order to serve large working set. It is difficult for DRAM （dynamic random access memory） based memory system to satisfy the memory capacity requirement due to its limited scalability and high energy consumption. Compared to DRAM, PCM （phase change memory） has better scalability, lower energy leakage, and non-volatility. PCM memory systems have become a hot topic of academic and industrial research. However, PCM technology has the following three drawbacks： long write latency, limited write endurance, and high write energy, which raises challenges to its adoption in practice. This paper surveys architectural research work to optimize PCM memory systems. First, this paper introduces the background of PCM. Then, it surveys research efforts on PCM memory systems in performance optimization, lifetime improving, and energy saving in detail, respectively. This paper also compares and summarizes these techniques from multiple dimensions. Finally, it concludes these optimization techniques and discusses possible research directions of PCM memory systems in future.
As the scaling of applications increases, the demand of main memory capacity increases in order to serve large working set. It is difficult for DRAM （dynamic random access memory） based memory system to satisfy the memory capacity requirement due to its limited scalability and high energy consumption. Compared to DRAM, PCM （phase change memory） has better scalability, lower energy leakage, and non-volatility. PCM memory systems have become a hot topic of academic and industrial research. However, PCM technology has the following three drawbacks： long write latency, limited write endurance, and high write energy, which raises challenges to its adoption in practice. This paper surveys architectural research work to optimize PCM memory systems. First, this paper introduces the background of PCM. Then, it surveys research efforts on PCM memory systems in performance optimization, lifetime improving, and energy saving in detail, respectively. This paper also compares and summarizes these techniques from multiple dimensions. Finally, it concludes these optimization techniques and discusses possible research directions of PCM memory systems in future.
基金
This work was supported by the National Basic Research 973 Program of China under Grant No. 2011CB302502, the National Natural Science Foundation of China under Grant No. 61379042, Huawei Research Program under Grant No. YB2013090048, and the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No. XDA06010401.
