PICO-RAM: A PVT-Insensitive Analog Compute-In-Memory SRAM Macro With In Situ Multi-Bit Charge Computing and 6T Thin-Cell-Compatible Layout
Analog compute-in-memory (CIM) in static random access memory (SRAM) is promising for
accelerating deep learning inference by circumventing the memory wall and exploiting ultra …
accelerating deep learning inference by circumventing the memory wall and exploiting ultra …
A multiply-less approximate SRAM compute-in-memory macro for neural-network inference
Compute-in-memory (CIM) is promising in reducing data movement energy and providing
large bandwidth for matrix-vector multiplies (MVMs). However, existing work still faces …
large bandwidth for matrix-vector multiplies (MVMs). However, existing work still faces …
The Landscape of Compute-near-memory and Compute-in-memory: A Research and Commercial Overview
In today's data-centric world, where data fuels numerous application domains, with machine
learning at the forefront, handling the enormous volume of data efficiently in terms of time …
learning at the forefront, handling the enormous volume of data efficiently in terms of time …
CiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool
Compute-In-Memory (CiM) is a promising solution to accelerate Deep Neural Networks
(DNNs) as it can avoid energy-intensive DNN weight movement and use memory arrays to …
(DNNs) as it can avoid energy-intensive DNN weight movement and use memory arrays to …
SSM-CIM: An Efficient CIM Macro Featuring Single-Step Multi-bit MAC Computation for CNN Edge Inference
H Zhang, S He, X Lu, X Guo, S Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Compute-in-memory (CIM) is a promising approach to solving the memory-wall problem
existing in traditional computing architectures. In this paper, we introduce SSM-CIM, a …
existing in traditional computing architectures. In this paper, we introduce SSM-CIM, a …
Scaling-CIM: eDRAM In-Memory-Computing Accelerator With Dynamic-Scaling ADC and Adaptive Analog Operation
This article presents Scaling-computing-in-memory (CIM), an energy-efficient embedded
dynamic random access memory (eDRAM)-based in-memory-computing (IMC) accelerator …
dynamic random access memory (eDRAM)-based in-memory-computing (IMC) accelerator …
A 28-nm 135.19 TOPS/W Bootstrapped-SRAM Compute-in-Memory Accelerator With Layer-Wise Precision and Sparsity
W Mao, D Liu, H Zhou, F Li, K Li, Q Wu… - … on Circuits and …, 2024 - ieeexplore.ieee.org
Artificial intelligence (AI) edge devices demand high energy efficiency as well as inference
accuracy. SRAM-based compute-in-memory (CIM) accelerators have great potential for …
accuracy. SRAM-based compute-in-memory (CIM) accelerators have great potential for …
A 28-nm 50.1-TOPS/W P-8T SRAM Compute-In-Memory Macro Design With BL Charge-Sharing-Based In-SRAM DAC/ADC Operations
This article presents a low-cost PMOS-based 8T (P-8T) static random access memory
(SRAM) compute-in-memory (CIM) macro that efficiently reduces the hardware cost …
(SRAM) compute-in-memory (CIM) macro that efficiently reduces the hardware cost …
Architectural Exploration of Application-Specific Resonant SRAM Compute-in-Memory (rCiM)
D Challagundla, I Bezzam, R Islam - arXiv preprint arXiv:2411.09546, 2024 - arxiv.org
While general-purpose computing follows Von Neumann's architecture, the data movement
between memory and processor elements dictates the processor's performance. The …
between memory and processor elements dictates the processor's performance. The …
Analog chip paves the way for sustainable AI
H Wang - 2023 - nature.com
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