Random access memory

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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
Author(s): Do Han Kim, Minyoung Jo, Gi Seok Kim, Dong Gyun Ha, Ung Bin Oh, Donghan Ko, Jiwoo Lee, Mingu Kang, Seong-Ook Jung

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 …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3623117
Publisher: IEEE

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Comprehensive Device to System Co-Design for SOT-MRAM at the 7 nm Node

Comprehensive Device to System Co-Design for SOT-MRAM at the 7 nm Node 150 150
Author(s): Piyush Kumar, Da Eun Shim, Azad Naeemi

Abstract:

This work presents a comprehensive spin-orbit torque (SOT)-based magnetic random access memory (MRAM) design at the 7 nm technology node, spanning from device-level characteristics to system-level power performance area (PPA). At the device level, we show the tradeoffs among the write current, error rate, and time, based on mircomagnetic simulations. …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 139 – 147
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3621279
Publisher: IEEE

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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
Author(s): Sadik Yasir Tauki, Rudra Biswas, Rakesh Acharya, Jiahui Duan, Rajiv Joshi, Kai Ni, Vijaykrishnan Narayanan

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 …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 148 – 156
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3619908
Publisher: IEEE

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Benchmarking of FERAM-Based Memory System by Optimizing Ferroelectric Device Model

Benchmarking of FERAM-Based Memory System by Optimizing Ferroelectric Device Model 150 150
Author(s): Mohammad Adnaan, Saeideh Alinezhad Chamazcoti, Emil Karimov, Marie Garcia Bardon, Francky Catthoor, Jan van Houdt, Azad Naeemi

Abstract:

We present a framework for design technology co-optimization (DTCO) of the main memory system with one transistor-one capacitor (1T1C) ferroelectric random access memory (FERAM) as an alternative to dynamic random access memory (DRAM). We start with the ferroelectric capacitor device model and perform array-level memory circuit simulation. Then, we …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 99 – 106
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3618883
Publisher: IEEE

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3-D Stacked HBM and Compute Accelerators for LLM: Optimizing Thermal Management and Power Delivery Efficiency

3-D Stacked HBM and Compute Accelerators for LLM: Optimizing Thermal Management and Power Delivery Efficiency 150 150
Author(s): Janak Sharda, Madison Manley, Jungyoun Kwak, Chinsung Park, Muhannad Bakir, Shimeng Yu

Abstract:

Advanced packaging is becoming essential for designing hardware accelerators for large language models (LLMs). Different architectures, such as 2.5-D integration of memory with logic, have been proposed; however, the bandwidth limits the throughput of the complete system. Recent works have proposed memory on logic systems, where high bandwidth memory (HBM) …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 116 – 122
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3617298
Publisher: IEEE

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A 180-nm Voltage-Controlled Magneto-Electric RAM With Sub-1-ns Switching Time

A 180-nm Voltage-Controlled Magneto-Electric RAM With Sub-1-ns Switching Time 150 150
Author(s): Haris Suhail, Haoran He, Vinod Kurian Jacob, Jiyue Yang, Kang L. Wang, Sudhakar Pamarti

Abstract:

Memory performance has emerged as a critical factor influencing both system speed and energy efficiency. However, conventional memory technologies such as embedded Flash (eFlash) and static RAM (SRAM) encounter significant scalability limitations beyond the 28-nm CMOS node. Among novel emerging memory technologies, spin-transfer-torque magnetic RAM (STT-MRAM) has gained prominence due …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3609342
Publisher: IEEE

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A 28-nm Computing-in-Memory Processor With Zig-Zag Backbone-Systolic CIM and Block-/Self-Gating CAM for NN/Recommendation Applications

A 28-nm Computing-in-Memory Processor With Zig-Zag Backbone-Systolic CIM and Block-/Self-Gating CAM for NN/Recommendation Applications 150 150
Author(s): Shengzhe Yan, Zhuoyu Dai, Zhaori Cong, Zeyu Guo, Yifan He, Wenyu Sun, Chunmeng Dou, Feng Zhang, Jinshan Yue, Yongpan Liu, Ming Liu

Abstract:

Computing-in-memory (CIM) chips have demonstrated promising energy efficiency for artificial intelligence (AI) applications such as neural networks (NNs), Transformer, and recommendation system (RecSys). However, several challenges still exist. First, a large gap between the macro and system-level CIM energy efficiency is observed. Second, several memory-dominate operations, such as embedding in …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 15
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3610539
Publisher: IEEE

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ROZK: An Energy-Efficient DNN Accelerator Based on Reconfigurable NoC and Local Zero-Skipping

ROZK: An Energy-Efficient DNN Accelerator Based on Reconfigurable NoC and Local Zero-Skipping 150 150
Author(s): Heetak Kim, Yunpyo Hong, Byungsoo Kim, Jongsun Park

Abstract:

Zero-skipping is a famous technique to improve the energy efficiency of deep neural network (DNN) accelerators. When the zero-skipping is realized with encoded data using lossless compression, irregular and unpredictable size of data due to inconsistent compression rate incurs several design issues including: 1) load imbalance from irregularity of data stored …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 12
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3604814
Publisher: IEEE

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MIX-ACIM: A 28-nm Mixed-Precision Analog Compute-in-Memory With Digital Feature Restoration for Vector-Matrix Multiplication

MIX-ACIM: A 28-nm Mixed-Precision Analog Compute-in-Memory With Digital Feature Restoration for Vector-Matrix Multiplication 150 150
Author(s): Wei-Chun Wang, Shida Zhang, Laith Shamieh, Narasimha Vasishta Kidambi, Isha Chakraborty, Saibal Mukhopadhyay

Abstract:

A mixed-precision analog compute-in-memory (Mix-ACIM) is presented for mixed-precision vector-matrix multiplication (VMM). The design features an all-analog current-domain fixed-point (FxP) VMM with floating-point conversion and feature restoration. A 28 nm CMOS test chip shows 41 TOPS/W and 24 TOPS/mm2 for FxP (8-bit input/weight and 12-bit output) and 24.18 TFLOPS/W and 3.3 …

Published in: IEEE Solid-State Circuits Letters
Page(s): 213 – 216
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3590757
Publisher: IEEE

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