受强制性开放获取政策约束的文章 - Hongwu Jiang了解详情
无法在其他位置公开访问的文章：9 篇
Compute-in-memory chips for deep learning: Recent trends and prospects
S Yu, H Jiang, S Huang, X Peng, A Lu
IEEE circuits and systems magazine 21 (3), 31-56, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
CIMAT: A compute-in-memory architecture for on-chip training based on transpose SRAM arrays
H Jiang, X Peng, S Huang, S Yu
IEEE Transactions on Computers 69 (7), 944-954, 2020
强制性开放获取政策： US National Science Foundation
A 40nm analog-input ADC-free compute-in-memory RRAM macro with pulse-width modulation between sub-arrays
H Jiang, W Li, S Huang, S Yu
2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and …, 2022
强制性开放获取政策： US Department of Defense
A 40nm RRAM compute-in-memory macro featuring on-chip write-verify and offset-cancelling ADC references
W Li, X Sun, H Jiang, S Huang, S Yu
ESSCIRC 2021-IEEE 47th European Solid State Circuits Conference (ESSCIRC), 79-82, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
NeuroSim validation with 40nm RRAM compute-in-memory macro
A Lu, X Peng, W Li, H Jiang, S Yu
2021 IEEE 3rd International Conference on Artificial Intelligence Circuits …, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
Secure XOR-CIM engine: Compute-in-memory SRAM architecture with embedded XOR encryption
S Huang, H Jiang, X Peng, W Li, S Yu
IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29 (12 …, 2021
强制性开放获取政策： US National Science Foundation
ENNA: An efficient neural network accelerator design based on ADC-free compute-in-memory subarrays
H Jiang, S Huang, W Li, S Yu
IEEE Transactions on Circuits and Systems I: Regular Papers 70 (1), 353-363, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
A 40nm RRAM compute-in-memory macro with parallelism-preserving ECC for iso-accuracy voltage scaling
W Li, J Read, H Jiang, S Yu
ESSCIRC 2022-IEEE 48th European Solid State Circuits Conference (ESSCIRC …, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
Achieving High In Situ Training Accuracy and Energy Efficiency with Analog Non-Volatile Synaptic Devices
S Huang, X Sun, X Peng, H Jiang, S Yu
ACM Transactions on Design Automation of Electronic Systems (TODAES) 27 (4 …, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
可在其他位置公开访问的文章：9 篇
DNN+ NeuroSim V2. 0: An end-to-end benchmarking framework for compute-in-memory accelerators for on-chip training
X Peng, S Huang, H Jiang, A Lu, S Yu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020
强制性开放获取政策： US National Science Foundation, US Department of Defense
NeuroSim simulator for compute-in-memory hardware accelerator: Validation and benchmark
A Lu, X Peng, W Li, H Jiang, S Yu
Frontiers in artificial intelligence 4, 659060, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
Analog-to-digital converter design exploration for compute-in-memory accelerators
H Jiang, W Li, S Huang, S Cosemans, F Catthoor, S Yu
IEEE Design & Test 39 (2), 48-55, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
A 40-nm MLC-RRAM compute-in-memory macro with sparsity control, on-chip write-verify, and temperature-independent ADC references
W Li, X Sun, S Huang, H Jiang, S Yu
IEEE Journal of Solid-State Circuits 57 (9), 2868-2877, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
Secure-RRAM: A 40nm 16kb compute-in-memory macro with reconfigurability, sparsity control, and embedded security
W Li, S Huang, X Sun, H Jiang, S Yu
2021 IEEE Custom Integrated Circuits Conference (CICC), 1-2, 2021
强制性开放获取政策： US Department of Defense
MINT: Mixed-precision RRAM-based in-memory training architecture
H Jiang, S Huang, X Peng, S Yu
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
强制性开放获取政策： US National Science Foundation, US Department of Defense
Overcoming challenges for achieving high in-situ training accuracy with emerging memories
S Huang, X Sun, X Peng, H Jiang, S Yu
2020 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2020
强制性开放获取政策： US National Science Foundation, US Department of Defense
Hardware-aware Quantization/Mapping Strategies for Compute-in-Memory Accelerators
S Huang, H Jiang, S Yu
ACM Transactions on Design Automation of Electronic Systems 28 (3), 1-23, 2023
强制性开放获取政策： US Department of Defense
Mac-ecc: In-situ error correction and its design methodology for reliable nvm-based compute-in-memory inference engine
W Li, J Read, H Jiang, S Yu
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 12 (4 …, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
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