This paper presents a tutorial and review of SRAM-based Compute-in-Memory (CIM) circuits, with a focus on both Digital CIM (DCIM) and Analog CIM (ACIM) implementations. We explore the fundamental concepts, architectures, and operational principles of CIM technology. The review compares DCIM and ACIM approaches, examining their respective advantages and challenges. DCIM offers high computational precision and process scaling benefits, while ACIM provides superior power and area efficiency, particularly for medium-precision applications. We analyze various ACIM implementations, including current-based, time-based, and charge-based approaches, with a detailed look at charge-based ACIMs. The paper also discusses emerging hybrid CIM architectures that combine DCIM and ACIM to leverage the strengths of both approaches.

翻译：本文对基于SRAM的存内计算（CIM）电路进行了系统性的教程式综述，重点涵盖数字存内计算（DCIM）与模拟存内计算（ACIM）两种实现方式。我们深入探讨了CIM技术的基本概念、体系架构及工作原理。本综述对比了DCIM与ACIM方案，剖析了各自的技术优势与挑战：DCIM具备高计算精度和工艺缩放优势，而ACIM则在功耗和面积效率方面表现更优，尤其适用于中等精度计算场景。我们系统分析了多种ACIM实现方案，包括基于电流、基于时间和基于电荷的方法，并对电荷型ACIM进行了重点剖析。本文还讨论了结合DCIM与ACIM优势的混合型CIM架构等新兴技术方向。