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    张章, 施刚, 王启帆, 马永波, 刘钢, 钱利波. 基于SRAM和NVM的存内计算技术综述[J]. 计算机研究与发展. DOI: 10.7544/issn1000-1239.202330364
    引用本文: 张章, 施刚, 王启帆, 马永波, 刘钢, 钱利波. 基于SRAM和NVM的存内计算技术综述[J]. 计算机研究与发展. DOI: 10.7544/issn1000-1239.202330364
    Zhang Zhang, Shi Gang, Wang Qifan, Ma Yongbo, Liu Gang, Qian Libo. Survey of In-Memory Computing Technology Based on SRAM and Non-Volatile Memory[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330364
    Citation: Zhang Zhang, Shi Gang, Wang Qifan, Ma Yongbo, Liu Gang, Qian Libo. Survey of In-Memory Computing Technology Based on SRAM and Non-Volatile Memory[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330364

    基于SRAM和NVM的存内计算技术综述

    Survey of In-Memory Computing Technology Based on SRAM and Non-Volatile Memory

    • 摘要: 集存储与计算于一身的快速低功耗存内计算架构,突破了存储与计算分离的传统冯·诺伊曼体系,解决了限制处理器算力的“内存墙”问题,成为新型计算架构的研究热点. 存内计算的基础器件包括高速且工艺成熟的静态随机存取存储器(static RAM,SRAM)、低功耗高响应且非易失的忆阻器(memristor)、高密度低静态功耗非易失的磁性随机存取存储器(magnetic RAM,MRAM). 研究者们基于上述器件完成大量存内计算研究,但是关于这些存内计算架构全面且系统总结的文献综述仍然缺失. 首先从SRAM、忆阻器、MRAM方向出发概述了不同器件的存内计算原理、当前存内计算架构发展状况和实际应用场景等. 然后针对当前存内计算架构存在的各种问题和挑战给出了现有解决方案和未来解决方向. 最后对基于以上器件的存内计算研究重点进行了总结并概述了目前的研究短板、展望未来的发展方向.

       

      Abstract: The fast and low-power in-memory computing architecture, which integrates memory and calculation, breaks through the traditional von-Neumann system that separates memory and calculation, and solves the problem of “memory wall” that limits the arithmetic power of the Professor, which has become a research hotspot of new computing architecture. The basic devices for in-memory computing include fast and mature Profess static random access memory (SRAM), low power, fast response and non-volatile memristor, and high density, low static power and non-volatile magnetic random access memory (MRAM). Up to the present, a great variety of in-memory computing studies have been proposed based on these devices, however, a systematic and comprehensive literature review on these in-memory computing architectures is still missing. In this paper, we first introduce the in-memory computing principles of different devices, the current development status of in-memory computing architectures, and the practical application scenarios from the three directions of SRAM, Memristor, and MRAM. Next, the existing solutions and the future directions for the problems and challenges of current in-memory computing architectures are given. Finally, this paper summarizes the research focus of in-memory computing based on the above devices, outline the shortcomings of the current research, and look forward to the future development direction.

       

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