支持逻辑电路辅助计算的相变存储系统设计

doi:10.16183/j.cnki.jsjtu.2018.01.014

上海交通大学学报（自然版） ›› 2018, Vol. 52 ›› Issue (1): 90-95.doi: 10.16183/j.cnki.jsjtu.2018.01.014

支持逻辑电路辅助计算的相变存储系统设计

李鸽子1，陈小刚1，陈后鹏1，焦圣品2，宋志棠1，陈邦明1

1. 中国科学院上海微系统与信息技术研究所信息功能材料国家重点实验室，上海 200050； 2. 上海天玑数据技术有限公司，上海 200233

出版日期:2018-01-01 发布日期:2018-01-01
基金资助:
中国科学院战略性先导科技专项（XDA09020402），国家重点基础研究发展规划（973）项目（2013CBA01900），国家集成电路重大专项（2009ZX02023-003），国家自然科学基金项目（61376006）

Logical Circuit Accelerated Computing for Phase Change Memory Based Storage System

LI Gezi1,CHEN Xiaogang1,CHEN Houpeng1,JIAO Shengpin2

1. State Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China; 2. Shanghai Phegda Data Technology Co., Ltd., Shanghai 200233, China

Online:2018-01-01 Published:2018-01-01

摘要/Abstract

摘要： 设计了一种支持逻辑电路辅助计算的相变存储系统，将计算密集型任务卸载至基于逻辑电路的相变存储器（PCM）中，以解决由于大量数据迁移而造成的传输瓶颈问题；同时，利用逻辑电路的并行执行能力来实现对数据的高效处理，并利用PCM的独特优势来提高系统的整体性能.结果表明，所提出的相变存储系统比传统的数据处理方式的性能更佳.

关键词: 相变存储器, 存储内计算, 现场可编程门阵列, 排序算法, 流式计算

Abstract: A phase change memory (PCM) based storage system with novel logical device is proposed, and it can off-load compute-intensive tasks from sever to the storage. In such a way, the proposed PCM-based storage system can avoid extra data transfer and improve efficiency of data processing with parallelism capability of logical device. Moreover, PCM promises to increase the overall system performance due to its unique features. Experimental results demonstrate that the proposed system is vastly superior to the traditional way.

Key words: phase change memory (PCM), in-storage processing (ISP), field-programmable gate array (FPGA), sorting algorithm, stream computing

中图分类号:

TP 333

李鸽子1，陈小刚1，陈后鹏1，焦圣品2，宋志棠1，陈邦明1. 支持逻辑电路辅助计算的相变存储系统设计[J]. 上海交通大学学报（自然版）, 2018, 52(1): 90-95.

LI Gezi1,CHEN Xiaogang1,CHEN Houpeng1,JIAO Shengpin2. Logical Circuit Accelerated Computing for Phase Change Memory Based Storage System[J]. Journal of Shanghai Jiaotong University, 2018, 52(1): 90-95.

参考文献

［1］HILBERT M, LOPEZ P. The world’s technological capacity to store, communicate, and compute information［J］. Science, 2011, 332: 60-65. ［2］孙大为, 张广艳, 郑纬民. 大数据流式计算: 关键技术及系统实例［J］. 软件学报，2014, 25(4): 839-862. SUN Dawei, ZHANG Guangyan, ZHENG Weimin. Big data stream computing: Technologies and instances［J］. Journal of Software, 2014, 25(4): 839-862. ［3］CAULFIELD A M, MOLLOV T I, EISNER L A, et al. Providing safe, user space access to fast, solid state disks［J］. Acm Sigplan Notices, 2012, 40(1): 387-400. ［4］黄震华, 张佳雯, 田春岐, 等. 基于排序学习的推荐算法研究综述［J］. 软件学报, 2016, 27(3): 691-713. HUANG Zhenhua, ZHANG Jiawen, TIAN Chunqi, et al. Survey on learning-to-rank based recommendation algorithms［J］. Journal of Software, 2016, 27(3): 691-713. ［5］YANG Y, YU P, GAN Y. Experimental study on the five sort algorithms［C］∥Second International Conference on Mechanic Automation and Control Engineering. Piscataway, USA: IEEE, 2011: 1314-1317. ［6］SKLYAROV V, SKLIAROVA I, MIHHAILOV D, et al. Implementation in FPGA of address-based data sorting［C］∥21st International Conference on Field Programmable Logic and Applications. Piscataway, USA: IEEE, 2011: 405-410. ［7］罗乐, 刘轶, 钱德沛. 内存计算技术研究综述［J］. 软件学报, 2016, 27(8): 2147-2167. LUO Le, LIU Yi, QIAN Depei. Survey on in-memory computing technology［J］. Journal of Software, 2016, 27(8): 2147-2167. ［8］DOLLER E, AKEL A, WANG J, et al. DataCenter 2020: Near-memory acceleration for data-oriented applications［C］∥Symposium on VLSI Circuits Digest of Technical Papers. Piscataway: IEEE, 2014: 1-4. ［9］KANG Y, KEE Y S, MILLER E L, et al. Enabling cost-effective data processing with smart SSD［C］∥Symposium on Mass Storage Systems and Technologies. Piscataway, USA: IEEE, 2013: 1-12. ［10］GRACIA-TINEDO R, SAMP J, GMEZ E Z, et al. Crystal: Software-defined storage for multi-tenant object stores［C］∥15th USENIX Conference on File and Storage Technologies (FAST). Berkeley, USA: USENIX, 2017: 243-256. ［11］DO J, KEE Y S, PATEL J M, et al. Query processing on smart SSDs: Opportunities and challenges［C］∥International Conference on Management of Data. New York, USA: ACM, 2013: 1221-1230. ［12］CAULFIELD A M, DE A, COBURN J, et al. Moneta: A high-performance storage array architecture for next-generation, non-volatile memories［C］∥43th Annual IEEE/ACM International Symposium on Microarchitecture. Piscataway, USA: IEEE, 2010: 385-395. ［13］YANG M C, KUO M F, TSAO C W, et al. A fifty-percent rule to minimize the energy consumption of PCM-based storage systems［C］∥19th International Conference on Embedded and Real-Time Computing Systems and Applications. Piscataway, USA: IEEE, 2013: 139-144. ［14］CHANG Y H, CHEN T Y, CHEN Y J, et al. Optimizing space utilization of file systems on PCM-based storage devices［C］∥Non-Volatile Memory Systems and Applications Symposium (NVMSA). Piscataway, USA: IEEE, 2014: 1-6. ［15］WOODS L, ISTVN Z, ALONSO G. An intelligent storage engine with support for advanced SQL offloading［J］. Proceedings of the VLDB Endowment, 2014, 7(11): 963-974. ［16］IBM/Netezza. The netezza data appliance architecture: A platform for high performance data warehousing and analytics ［EB/OL］. (2016-02-08) ［2016-12-01］. http:∥www.redbooks.ibm.com/abstracts/redp4725.html. ［17］CORMEN T H, LEISERSON C E, RIVEST R L. Introduce to algorithms［M］. 2nd ed. Cambridge, England: MIT Press, 2001.

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支持逻辑电路辅助计算的相变存储系统设计

Logical Circuit Accelerated Computing for Phase Change Memory Based Storage System

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