{"title":"基于均匀场效应效应的矩阵-向量乘法和关联搜索时域内存计算结构","authors":"Xunzhao Yin;Qingrong Huang;Hamza Errahmouni Barkam;Franz Müller;Shan Deng;Alptekin Vardar;Sourav De;Zhouhang Jiang;Mohsen Imani;Ulf Schlichtmann;Xiaobo Sharon Hu;Cheng Zhuo;Thomas Kämpfe;Kai Ni","doi":"10.1109/TCAD.2024.3492994","DOIUrl":null,"url":null,"abstract":"Matrix-vector multiplication (MVM) and content-based search are two key operations in many machine learning workloads. This article proposes a ferroelectric FET (FeFET) time-domain compute-in-memory (TD-CiM) array that can accelerate both operations in a homogeneous fabric. We demonstrate that 1) the AND and xor/XNOR logic functions required by MVM and content-based search can be realized using a single compute-in-memory (CiM) cell composed of 2FeFETs connected in series; 2) an inverter chain-based TD-CiM array along with a two-phase time-domain computation principle of the TD-CiM can be employed to implement the MVM and content-based search functions; 3) a signal delay-to-digital output conversion can be implemented by associating a loading capacitor with each stage of the inverter chain-based TD-CiM array, ensuring the full digital compatibility; and 4) the proposed 2FeFET cell and inverter chain-based TD-CiM array are robust against FeFET variation according to our comprehensive theoretical and experimental validation. We show how the FeFET TD-CiM can be exploited to accelerate hyperdimensional computing (HDC) and adjusted to process different tasks through dynamic and fine-grained resource allocation. HDC application benchmarking results show that the proposed FeFET-based TD-CiM offers on average <inline-formula> <tex-math>$106\\times $ </tex-math></inline-formula>/<inline-formula> <tex-math>$63\\times $ </tex-math></inline-formula> energy reduction/speedup compared to GPU-based implementation. With more than 8500 TOPS/W energy-efficiency, the proposed FeFET-based TD-CiM exhibits huge potential as a processing fabric for various memory-intensive applications.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"44 5","pages":"1856-1868"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Homogeneous FeFET-Based Time-Domain Compute-in-Memory Fabric for Matrix-Vector Multiplication and Associative Search\",\"authors\":\"Xunzhao Yin;Qingrong Huang;Hamza Errahmouni Barkam;Franz Müller;Shan Deng;Alptekin Vardar;Sourav De;Zhouhang Jiang;Mohsen Imani;Ulf Schlichtmann;Xiaobo Sharon Hu;Cheng Zhuo;Thomas Kämpfe;Kai Ni\",\"doi\":\"10.1109/TCAD.2024.3492994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Matrix-vector multiplication (MVM) and content-based search are two key operations in many machine learning workloads. This article proposes a ferroelectric FET (FeFET) time-domain compute-in-memory (TD-CiM) array that can accelerate both operations in a homogeneous fabric. We demonstrate that 1) the AND and xor/XNOR logic functions required by MVM and content-based search can be realized using a single compute-in-memory (CiM) cell composed of 2FeFETs connected in series; 2) an inverter chain-based TD-CiM array along with a two-phase time-domain computation principle of the TD-CiM can be employed to implement the MVM and content-based search functions; 3) a signal delay-to-digital output conversion can be implemented by associating a loading capacitor with each stage of the inverter chain-based TD-CiM array, ensuring the full digital compatibility; and 4) the proposed 2FeFET cell and inverter chain-based TD-CiM array are robust against FeFET variation according to our comprehensive theoretical and experimental validation. We show how the FeFET TD-CiM can be exploited to accelerate hyperdimensional computing (HDC) and adjusted to process different tasks through dynamic and fine-grained resource allocation. HDC application benchmarking results show that the proposed FeFET-based TD-CiM offers on average <inline-formula> <tex-math>$106\\\\times $ </tex-math></inline-formula>/<inline-formula> <tex-math>$63\\\\times $ </tex-math></inline-formula> energy reduction/speedup compared to GPU-based implementation. With more than 8500 TOPS/W energy-efficiency, the proposed FeFET-based TD-CiM exhibits huge potential as a processing fabric for various memory-intensive applications.\",\"PeriodicalId\":13251,\"journal\":{\"name\":\"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems\",\"volume\":\"44 5\",\"pages\":\"1856-1868\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10745588/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10745588/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
A Homogeneous FeFET-Based Time-Domain Compute-in-Memory Fabric for Matrix-Vector Multiplication and Associative Search
Matrix-vector multiplication (MVM) and content-based search are two key operations in many machine learning workloads. This article proposes a ferroelectric FET (FeFET) time-domain compute-in-memory (TD-CiM) array that can accelerate both operations in a homogeneous fabric. We demonstrate that 1) the AND and xor/XNOR logic functions required by MVM and content-based search can be realized using a single compute-in-memory (CiM) cell composed of 2FeFETs connected in series; 2) an inverter chain-based TD-CiM array along with a two-phase time-domain computation principle of the TD-CiM can be employed to implement the MVM and content-based search functions; 3) a signal delay-to-digital output conversion can be implemented by associating a loading capacitor with each stage of the inverter chain-based TD-CiM array, ensuring the full digital compatibility; and 4) the proposed 2FeFET cell and inverter chain-based TD-CiM array are robust against FeFET variation according to our comprehensive theoretical and experimental validation. We show how the FeFET TD-CiM can be exploited to accelerate hyperdimensional computing (HDC) and adjusted to process different tasks through dynamic and fine-grained resource allocation. HDC application benchmarking results show that the proposed FeFET-based TD-CiM offers on average $106\times $ /$63\times $ energy reduction/speedup compared to GPU-based implementation. With more than 8500 TOPS/W energy-efficiency, the proposed FeFET-based TD-CiM exhibits huge potential as a processing fabric for various memory-intensive applications.
期刊介绍:
The purpose of this Transactions is to publish papers of interest to individuals in the area of computer-aided design of integrated circuits and systems composed of analog, digital, mixed-signal, optical, or microwave components. The aids include methods, models, algorithms, and man-machine interfaces for system-level, physical and logical design including: planning, synthesis, partitioning, modeling, simulation, layout, verification, testing, hardware-software co-design and documentation of integrated circuit and system designs of all complexities. Design tools and techniques for evaluating and designing integrated circuits and systems for metrics such as performance, power, reliability, testability, and security are a focus.