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2020 – today
- 2024
[c28]Hidehiro Fujiwara, Haruki Mori, Wei-Chang Zhao, Kinshuk Khare, Cheng-En Lee, Xiaochen Peng, Vineet Joshi, Chao-Kai Chuang, Shu-Huan Hsu, Takeshi Hashizume, Toshiaki Naganuma, Chen-Hung Tien, Yao-Yi Liu, Yen-Chien Lai, Chia-Fu Lee, Tan-Li Chou, Kerem Akarvardar, Saman Adham, Yih Wang
, Yu-Der Chih, Yen-Huei Chen, Hung-Jen Liao, Tsung-Yung Jonathan Chang:
34.4 A 3nm, 32.5TOPS/W, 55.0TOPS/mm2 and 3.78Mb/mm2 Fully-Digital Compute-in-Memory Macro Supporting INT12 × INT12 with a Parallel-MAC Architecture and Foundry 6T-SRAM Bit Cell. ISSCC 2024: 572-574- [c27]Ankit Kaul, Madison Manley, James Read, Yandong Luo, Xiaochen Peng, Shimeng Yu, Muhannad S. Bakir:
Co-Optimization for Robust Power Delivery Design in 3D-Heterogeneous Integration of Compute In-Memory Accelerators. VLSI Technology and Circuits 2024: 1-2 - 2022
- [b1]Xiaochen Peng:
Benchmark Framework for 2-D/3-D Integrated Compute-in-Memory Based Machine Learning Accelerator. Georgia Institute of Technology, Atlanta, GA, USA, 2022 - [j13]Shanshi Huang, Xiaoyu Sun, Xiaochen Peng, Hongwu Jiang, Shimeng Yu:
Achieving High In Situ Training Accuracy and Energy Efficiency with Analog Non-Volatile Synaptic Devices. ACM Trans. Design Autom. Electr. Syst. 27(4): 37:1-37:19 (2022) - 2021
- [j12]Anni Lu, Xiaochen Peng, Wantong Li, Hongwu Jiang, Shimeng Yu:
NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark. Frontiers Artif. Intell. 4: 659060 (2021) - [j11]Xiaochen Peng, Shanshi Huang, Hongwu Jiang, Anni Lu, Shimeng Yu:
DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-Chip Training. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(11): 2306-2319 (2021) - [j10]Shimeng Yu, Wonbo Shim, Xiaochen Peng, Yandong Luo:
RRAM for Compute-in-Memory: From Inference to Training. IEEE Trans. Circuits Syst. I Regul. Pap. 68(7): 2753-2765 (2021) - [j9]Jian Meng, Li Yang, Xiaochen Peng, Shimeng Yu, Deliang Fan, Jae-Sun Seo:
Structured Pruning of RRAM Crossbars for Efficient In-Memory Computing Acceleration of Deep Neural Networks. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1576-1580 (2021) - [j8]Anni Lu, Xiaochen Peng, Yandong Luo, Shanshi Huang, Shimeng Yu:
A Runtime Reconfigurable Design of Compute-in-Memory-Based Hardware Accelerator for Deep Learning Inference. ACM Trans. Design Autom. Electr. Syst. 26(6): 45:1-45:18 (2021) - [j7]Shanshi Huang, Hongwu Jiang, Xiaochen Peng, Wantong Li, Shimeng Yu:
Secure XOR-CIM Engine: Compute-In-Memory SRAM Architecture With Embedded XOR Encryption. IEEE Trans. Very Large Scale Integr. Syst. 29(12): 2027-2039 (2021) - [c26]Ankit Kaul, Yandong Luo, Xiaochen Peng, Shimeng Yu, Muhannad S. Bakir:
Thermal Reliability Considerations of Resistive Synaptic Devices for 3D CIM System Performance. 3DIC 2021: 1-5 - [c25]Anni Lu, Xiaochen Peng, Wantong Li, Hongwu Jiang, Shimeng Yu:
NeuroSim Validation with 40nm RRAM Compute-in-Memory Macro. AICAS 2021: 1-4 - [c24]Anni Lu, Xiaochen Peng, Shimeng Yu:
Compute-in-RRAM with Limited On-chip Resources. AICAS 2021: 1-4 - [c23]Anni Lu, Xiaochen Peng, Yandong Luo, Shanshi Huang, Shimeng Yu:
A Runtime Reconfigurable Design of Compute-in-Memory based Hardware Accelerator. DATE 2021: 932-937 - [c22]Shimeng Yu, Wonbo Shim, Jae Hur, Yuan-chun Luo, Gihun Choe, Wantong Li, Anni Lu, Xiaochen Peng:
Compute-in-Memory: From Device Innovation to 3D System Integration. ESSDERC 2021: 21-28 - [c21]Wonbo Shim, Jian Meng, Xiaochen Peng, Jae-sun Seo, Shimeng Yu:
Impact of Multilevel Retention Characteristics on RRAM based DNN Inference Engine. IRPS 2021: 1-4 - [c20]Shanshi Huang, Xiaochen Peng, Hongwu Jiang, Yandong Luo, Shimeng Yu:
Exploiting Process Variations to Protect Machine Learning Inference Engine from Chip Cloning. ISCAS 2021: 1-5 - [c19]Panni Wang, Xiaochen Peng, Wriddhi Chakraborty, Asif Khan, Suman Datta, Shimeng Yu:
Cryogenic Performance for Compute-in-Memory Based Deep Neural Network Accelerator. ISCAS 2021: 1-4 - 2020
- [j6]Hongwu Jiang, Xiaochen Peng, Shanshi Huang, Shimeng Yu:
CIMAT: A Compute-In-Memory Architecture for On-chip Training Based on Transpose SRAM Arrays. IEEE Trans. Computers 69(7): 944-954 (2020) - [j5]Xiaochen Peng, Rui Liu, Shimeng Yu:
Optimizing Weight Mapping and Data Flow for Convolutional Neural Networks on Processing-in-Memory Architectures. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 67-I(4): 1333-1343 (2020) - [j4]Anni Lu, Xiaochen Peng, Yandong Luo, Shimeng Yu:
Benchmark of the Compute-in-Memory-Based DNN Accelerator With Area Constraint. IEEE Trans. Very Large Scale Integr. Syst. 28(9): 1945-1952 (2020) - [c18]Shimeng Yu, Xiaoyu Sun, Xiaochen Peng, Shanshi Huang:
Compute-in-Memory with Emerging Nonvolatile-Memories: Challenges and Prospects. CICC 2020: 1-4 - [c17]Hongwu Jiang, Shanshi Huang, Xiaochen Peng, Jian-Wei Su, Yen-Chi Chou, Wei-Hsing Huang, Ta-Wei Liu, Ruhui Liu, Meng-Fan Chang, Shimeng Yu:
A Two-way SRAM Array based Accelerator for Deep Neural Network On-chip Training. DAC 2020: 1-6 - [c16]Shanshi Huang, Xiaoyu Sun, Xiaochen Peng, Hongwu Jiang, Shimeng Yu:
Overcoming Challenges for Achieving High in-situ Training Accuracy with Emerging Memories. DATE 2020: 1025-1030 - [c15]Shanshi Huang, Hongwu Jiang, Xiaochen Peng, Wantong Li, Shimeng Yu:
XOR-CIM: Compute-In-Memory SRAM Architecture with Embedded XOR Encryption. ICCAD 2020: 77:1-77:6 - [c14]Hongwu Jiang, Shanshi Huang, Xiaochen Peng, Shimeng Yu:
MINT: Mixed-Precision RRAM-Based IN-Memory Training Architecture. ISCAS 2020: 1-5 - [c13]Yandong Luo, Xiaochen Peng, Ryan Hatcher, Titash Rakshit, Jorge Kittl, Mark S. Rodder, Jae-Sun Seo, Shimeng Yu:
A Variation Robust Inference Engine Based on STT-MRAM with Parallel Read-Out. ISCAS 2020: 1-5 - [c12]Wonbo Shim, Hongwu Jiang, Xiaochen Peng, Shimeng Yu:
Architectural Design of 3D NAND Flash based Compute-in-Memory for Inference Engine. MEMSYS 2020: 77-85 - [i1]Xiaochen Peng, Shanshi Huang, Hongwu Jiang, Anni Lu, Shimeng Yu:
DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-chip Training. CoRR abs/2003.06471 (2020)
2010 – 2019
- 2019
- [j3]Manqing Mao, Xiaochen Peng, Rui Liu, Jingtao Li, Shimeng Yu, Chaitali Chakrabarti:
MAX2: An ReRAM-Based Neural Network Accelerator That Maximizes Data Reuse and Area Utilization. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 398-410 (2019) - [c11]Wenqiang Zhang, Xiaochen Peng, Huaqiang Wu, Bin Gao, Hu He, Youhui Zhang, Shimeng Yu, He Qian:
Design Guidelines of RRAM based Neural-Processing-Unit: A Joint Device-Circuit-Algorithm Analysis. DAC 2019: 140 - [c10]Yandong Luo, Xiaochen Peng, Shimeng Yu:
MLP+NeuroSimV3.0: Improving On-chip Learning Performance with Device to Algorithm Optimizations. ICONS 2019: 1:1-1:7 - [c9]Xiaochen Peng, Rui Liu, Shimeng Yu:
Optimizing Weight Mapping and Data Flow for Convolutional Neural Networks on RRAM Based Processing-In-Memory Architecture. ISCAS 2019: 1-5 - [c8]Xiaochen Peng, Minkyu Kim, Xiaoyu Sun, Shihui Yin, Titash Rakshit, Ryan M. Hatcher, Jorge A. Kittl, Jae-sun Seo, Shimeng Yu:
Inference engine benchmarking across technological platforms from CMOS to RRAM. MEMSYS 2019: 471-479 - [c7]Hongwu Jiang, Xiaochen Peng, Shanshi Huang, Shimeng Yu:
CIMAT: a transpose SRAM-based compute-in-memory architecture for deep neural network on-chip training. MEMSYS 2019: 490-496 - 2018
- [j2]Pai-Yu Chen, Xiaochen Peng, Shimeng Yu:
NeuroSim: A Circuit-Level Macro Model for Benchmarking Neuro-Inspired Architectures in Online Learning. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(12): 3067-3080 (2018) - [j1]Rui Liu, Pai-Yu Chen, Xiaochen Peng, Shimeng Yu:
X-Point PUF: Exploiting Sneak Paths for a Strong Physical Unclonable Function Design. IEEE Trans. Circuits Syst. I Regul. Pap. 65-I(10): 3459-3468 (2018) - [c6]Xiaochen Peng, Shimeng Yu:
Benchmark of RRAM based Architectures for Dot-Product Computation. APCCAS 2018: 378-381 - [c5]Xiaoyu Sun, Xiaochen Peng, Pai-Yu Chen, Rui Liu, Jae-sun Seo, Shimeng Yu:
Fully parallel RRAM synaptic array for implementing binary neural network with (+1, -1) weights and (+1, 0) neurons. ASP-DAC 2018: 574-579 - [c4]Rui Liu, Xiaochen Peng, Xiaoyu Sun, Win-San Khwa, Xin Si, Jia-Jing Chen, Jia-Fang Li, Meng-Fan Chang, Shimeng Yu:
Parallelizing SRAM arrays with customized bit-cell for binary neural networks. DAC 2018: 21:1-21:6 - [c3]Xiaoyu Sun, Shihui Yin, Xiaochen Peng, Rui Liu, Jae-sun Seo, Shimeng Yu:
XNOR-RRAM: A scalable and parallel resistive synaptic architecture for binary neural networks. DATE 2018: 1423-1428 - [c2]Jiyong Woo, Xiaochen Peng, Shimeng Yu:
Design Considerations of Selector Device in Cross-Point RRAM Array for Neuromorphic Computing. ISCAS 2018: 1-4 - [c1]Manqing Mao, Xiaoyu Sun, Xiaochen Peng, Shimeng Yu, Chaitali Chakrabarti:
A Versatile ReRAM-based Accelerator for Convolutional Neural Networks. SiPS 2018: 211-216
Coauthor Index
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last updated on 2024-10-18 20:30 CEST by the dblp team
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