MagCiM: A Flexible and Non-Volatile Computing-in-Memory Processor for Energy-Efficient Logic Computation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3159967
Abstract: This paper presents a high-performance and energy efficient processor exploiting a Magnetoresistive-based Computing-in-Memory array architecture (so-called MagCiM processor), to perform Boolean logic functions on operands stored in a memory array. The proposed processor efficiently addresses… read more here.
Keywords: magcim; processor; memory; energy efficient ... See more keywords
D-NAT: Data-Driven Non-Ideality Aware Training Framework for Fabricated Computing-In-Memory Macros
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"
DOI: 10.1109/jetcas.2022.3171268
Abstract: To enable energy-efficient computation for deep neural networks (DNNs) at edge, computing-in-memory (CIM) is proposed to reduce the energy costs during intense off-chip memory access. However, CIM is prone to multiply-accumulate (MAC) errors due to… read more here.
Keywords: non idealities; framework; data driven; driven non ... See more keywords
A 28 nm 81 Kb 59–95.3 TOPS/W 4T2R ReRAM Computing-in-Memory Accelerator With Voltage-to-Time-to-Digital Based Output
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"
DOI: 10.1109/jetcas.2022.3196678
Abstract: Computing-in-memory (CIM) based on Resistive RAM (ReRAM) can effectively improve the energy efficiency and throughput of artificial intelligence (AI) edge devices. However, due to the complex hardware structure and the non-ideal factors of the circuit,… read more here.
Keywords: reram; output; accelerator; energy efficiency ... See more keywords
A 40-nm, 64-Kb, 56.67 TOPS/W Voltage-Sensing Computing-In-Memory/Digital RRAM Macro Supporting Iterative Write With Verification and Online Read-Disturb Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Solid-State Circuits"
DOI: 10.1109/jssc.2021.3101209
Abstract: Computing-in-memory (CIM) architectures have gained importance in achieving high-throughput energy-efficient artificial intelligence (AI) systems. Resistive RAM (RRAM) is a promising candidate for CIM architectures due to a multiply-and-accumulate (MAC)-friendly structure, high bit density, compatibility with… read more here.
Keywords: macro supporting; voltage sensing; rram macro; digital rram ... See more keywords
Accuracy Optimization With the Framework of Non-Volatile Computing-In-Memory Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2021.3124553
Abstract: Computing-in-memory (CIM) is a new architecture which is more energy-efficient than the Von Neumann architecture due to the fact that it performs calculation in the memory units which can reduce a large amount of data… read more here.
Keywords: computing memory; framework; accuracy optimization; memory ... See more keywords
VSDCA: A Voltage Sensing Differential Column Architecture Based on 1T2R RRAM Array for Computing-in-Memory Accelerators
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2022.3186024
Abstract: Non-volatile memory (NVM) such as RRAM and PCM has become the key component in high energy efficiency computing-in-memory (CIM) architectures. However, the computing accuracy and energy efficiency improvement of conventional 1T1R RRAM array based current… read more here.
Keywords: rram array; sensing differential; voltage sensing; memory ... See more keywords
HD-CIM: Hybrid-Device Computing-In-Memory Structure Based on MRAM and SRAM to Reduce Weight Loading Energy of Neural Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2022.3199440
Abstract: SRAM based computing-in-memory (SRAM-CIM) techniques have been widely studied for neural networks (NNs) to solve the “Von Neumann bottleneck”. However, as the scale of the NN model increasingly expands, the weight cannot be fully stored… read more here.
Keywords: neural networks; sram; energy; memory ... See more keywords
Bit-Aware Fault-Tolerant Hybrid Retraining and Remapping Schemes for RRAM-Based Computing-in-Memory Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2022.3163177
Abstract: Non-volatile computing-in-memory (nvCIM) has become one of the most efficient methods to deal with increasingly complicated neural networks compared to the traditional von Neumann architecture. However, due to the immature fabrication issues, the yield of… read more here.
Keywords: bit aware; aware fault; fault; fault tolerant ... See more keywords
CIMulator: A Computing in Memory Emulator Framework
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2022.3193673
Abstract: In this brief, we present CIMulator, an open-source, extensible modeling, simulation, and emulation framework for on-chip digital Computing-In-Memory (CIM) design and assessment. Featuring a synthesizable Register Transfer Level (RTL) model, CIMulator encapsulates the fundamental in-memory… read more here.
Keywords: cimulator; framework; cim; memory ... See more keywords
A Multilevel Cell STT-MRAM-Based Computing In-Memory Accelerator for Binary Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Magnetics"
DOI: 10.1109/tmag.2018.2848625
Abstract: Due to additive operation’s dominated computation and simplified network in binary convolutional neural network (BCNN), it is promising for Internet of Things scenarios which demand ultralow power consumption. By means of fully exploiting the in-memory… read more here.
Keywords: network; binary convolutional; stt mram; convolutional neural ... See more keywords
Design of an Area-Efficient Computing in Memory Platform Based on STT-MRAM
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Magnetics"
DOI: 10.1109/tmag.2020.3016741
Abstract: In the era of big data, the memory wall between the processor and the memory as well as leakage current have become major bottlenecks of the traditional CMOS-based Von-Neumann computer architecture. Computing-in-memory (CiM) based on… read more here.
Keywords: memory; platform; stt mram; design area ... See more keywords