compute-in-memory (CIM)

DPe-CIM: A 4T-1C Dual-Port eDRAM-Based Compute-in-Memory for Simultaneous Computing and Refresh With Adaptive Refresh and Data Conversion Reduction Scheme

DPe-CIM: A 4T-1C Dual-Port eDRAM-Based Compute-in-Memory for Simultaneous Computing and Refresh With Adaptive Refresh and Data Conversion Reduction Scheme 150 150

Abstract:

This article presents DPe-CIM, a 4T-1C dual-port embedded dynamic random access memory (eDRAM)-based compute-in-memory (CIM) macro with adaptive refresh and data conversion reduction. DPe-CIM proposes four key features that improve area and energy efficiency: 1) dual-port eDRAM cell (DPC) separates the multiply-and-accumulate (MAC) and refresh ports, enabling simultaneous MAC …

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1.58-b FeFET-Based Ternary Neural Networks: Achieving Robust Compute-In-Memory With Weight-Input Transformations

1.58-b FeFET-Based Ternary Neural Networks: Achieving Robust Compute-In-Memory With Weight-Input Transformations 150 150

Abstract:

Ternary weight neural networks (TWNs), with weights quantized to three states (−1, 0, and 1), have emerged as promising solutions for resource-constrained edge artificial intelligence (AI) platforms due to their high energy efficiency with acceptable inference accuracy. Further energy savings can be achieved with TWN accelerators utilizing techniques such as compute-in-memory (CiM) and …

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Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs

Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs 150 150

Abstract:

Ferroelectric random access memory (FeRAM) is a promising candidate for energy-efficient nonvolatile memory, particularly for logic-in-memory and compute-in-memory (CIM) applications. Among the available cell architectures, One-Transistor–n-Capacitor (1T-nC) and two-transistor–n-capacitor (2T-nC) FeRAMs each offer distinct trade-offs in density, scalability, and reliability. In this work, we present a comparative study …

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