ReNEW: Enhancing lifetime for ReRAM crossbar based neural network accelerators
With analog current accumulation feature, resistive memory (ReRAM) crossbars are widely
studied to accelerate neural network applications. The ReRAM crossbar based accelerators …
studied to accelerate neural network applications. The ReRAM crossbar based accelerators …
On minimizing analog variation errors to resolve the scalability issue of reram-based crossbar accelerators
Crossbar accelerators with a resistive random-access memory (ReRAM) are a promising
solution for accelerating neural network applications. The advantages of achieving high …
solution for accelerating neural network applications. The advantages of achieving high …
Towards state-aware computation in ReRAM neural networks
Resistive RAM (ReRAM) is a promising device to realize the Computing in Memory (CiM)
architecture, suitable for power-constrained IoT systems. Because of low leakage, the dot …
architecture, suitable for power-constrained IoT systems. Because of low leakage, the dot …
Att: A fault-tolerant reram accelerator for attention-based neural networks
H Guo, L Peng, J Zhang, Q Chen… - 2020 IEEE 38th …, 2020 - ieeexplore.ieee.org
Crossbar-based resistive RAM has been widely used in deep learning accelerator designs
because it largely eliminates weight movement between memory and processing units. The …
because it largely eliminates weight movement between memory and processing units. The …
Exploring bit-slice sparsity in deep neural networks for efficient ReRAM-based deployment
Emerging resistive random-access memory (ReRAM) has recently been intensively
investigated to accelerate the processing of deep neural networks (DNNs). Due to the in-situ …
investigated to accelerate the processing of deep neural networks (DNNs). Due to the in-situ …
XB-SIM∗: A simulation framework for modeling and exploration of ReRAM-based CNN acceleration design
X Fei, Y Zhang, W Zheng - Tsinghua Science and Technology, 2020 - ieeexplore.ieee.org
Resistive Random Access Memory (ReRAM)-based neural network accelerators have
potential to surpass their digital counterparts in computational efficiency and performance …
potential to surpass their digital counterparts in computational efficiency and performance …
Mixed size crossbar based RRAM CNN accelerator with overlapped mapping method
Convolutional Neural Networks (CNNs) play a vital role in machine learning. CNNs are
typically both computing and memory intensive. Emerging resistive random-access …
typically both computing and memory intensive. Emerging resistive random-access …
CompRRAE: RRAM-based convolutional neural network accelerator with r educed computations through ar untime a ctivation e stimation
Recently Resistive-RAM (RRAM) crossbar has been used in the design of the accelerator of
convolutional neural networks (CNNs) to solve the memory wall issue. However, the …
convolutional neural networks (CNNs) to solve the memory wall issue. However, the …
A thermal-aware optimization framework for ReRAM-based deep neural network acceleration
Resistive RAM (ReRAM) is widely regarded as a promising platform for deep neural network
(DNN) acceleration. However, the ReRAM device suffers from severe thermal problems that …
(DNN) acceleration. However, the ReRAM device suffers from severe thermal problems that …
Offline training-based mitigation of IR drop for ReRAM-based deep neural network accelerators
S Lee, ME Fouda, J Lee, AM Eltawil… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, resistive RAM (ReRAM)-based hardware accelerators showed unprecedented
performance compared the digital accelerators. Technology scaling causes an inevitable …
performance compared the digital accelerators. Technology scaling causes an inevitable …