Xiaochen Peng
Orcid: 0000-0001-6148-7711
According to our database1,
Xiaochen Peng
authored at least 42 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Co-Optimization for Robust Power Delivery Design in 3D-Heterogeneous Integration of Compute In-Memory Accelerators.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits 2024, 2024
34.4 A 3nm, 32.5TOPS/W, 55.0TOPS/mm<sup>2</sup> and 3.78Mb/mm<sup>2</sup> Fully-Digital Compute-in-Memory Macro Supporting INT12 × INT12 with a Parallel-MAC Architecture and Foundry 6T-SRAM Bit Cell.
Proceedings of the IEEE International Solid-State Circuits Conference, 2024
2022
Benchmark Framework for 2-D/3-D Integrated Compute-in-Memory Based Machine Learning Accelerator.
PhD thesis, 2022
Achieving High In Situ Training Accuracy and Energy Efficiency with Analog Non-Volatile Synaptic Devices.
ACM Trans. Design Autom. Electr. Syst., 2022
2021
Secure XOR-CIM Engine: Compute-In-Memory SRAM Architecture With Embedded XOR Encryption.
IEEE Trans. Very Large Scale Integr. Syst., 2021
A Runtime Reconfigurable Design of Compute-in-Memory-Based Hardware Accelerator for Deep Learning Inference.
ACM Trans. Design Autom. Electr. Syst., 2021
Structured Pruning of RRAM Crossbars for Efficient In-Memory Computing Acceleration of Deep Neural Networks.
IEEE Trans. Circuits Syst. II Express Briefs, 2021
IEEE Trans. Circuits Syst. I Regul. Pap., 2021
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., 2021
NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark.
Frontiers Artif. Intell., 2021
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021
Exploiting Process Variations to Protect Machine Learning Inference Engine from Chip Cloning.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021
Proceedings of the IEEE International Reliability Physics Symposium, 2021
Proceedings of the 51st IEEE European Solid-State Device Research Conference, 2021
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021
Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021
Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021
Thermal Reliability Considerations of Resistive Synaptic Devices for 3D CIM System Performance.
Proceedings of the IEEE International 3D Systems Integration Conference, 2021
2020
IEEE Trans. Very Large Scale Integr. Syst., 2020
Optimizing Weight Mapping and Data Flow for Convolutional Neural Networks on Processing-in-Memory Architectures.
IEEE Trans. Circuits Syst. I Fundam. Theory Appl., 2020
CIMAT: A Compute-In-Memory Architecture for On-chip Training Based on Transpose SRAM Arrays.
IEEE Trans. Computers, 2020
Proceedings of the MEMSYS 2020: The International Symposium on Memory Systems, 2020
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020
Overcoming Challenges for Achieving High in-situ Training Accuracy with Emerging Memories.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020
Proceedings of the 2020 IEEE Custom Integrated Circuits Conference, 2020
2019
MAX<sup>2</sup>: An ReRAM-Based Neural Network Accelerator That Maximizes Data Reuse and Area Utilization.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2019
Proceedings of the International Symposium on Memory Systems, 2019
CIMAT: a transpose SRAM-based compute-in-memory architecture for deep neural network on-chip training.
Proceedings of the International Symposium on Memory Systems, 2019
Optimizing Weight Mapping and Data Flow for Convolutional Neural Networks on RRAM Based Processing-In-Memory Architecture.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2019
MLP+NeuroSimV3.0: Improving On-chip Learning Performance with Device to Algorithm Optimizations.
Proceedings of the International Conference on Neuromorphic Systems, 2019
Design Guidelines of RRAM based Neural-Processing-Unit: A Joint Device-Circuit-Algorithm Analysis.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019
2018
X-Point PUF: Exploiting Sneak Paths for a Strong Physical Unclonable Function Design.
IEEE Trans. Circuits Syst. I Regul. Pap., 2018
NeuroSim: A Circuit-Level Macro Model for Benchmarking Neuro-Inspired Architectures in Online Learning.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018
Proceedings of the 2018 IEEE International Workshop on Signal Processing Systems, 2018
Design Considerations of Selector Device in Cross-Point RRAM Array for Neuromorphic Computing.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018
XNOR-RRAM: A scalable and parallel resistive synaptic architecture for binary neural networks.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018
Proceedings of the 55th Annual Design Automation Conference, 2018
Fully parallel RRAM synaptic array for implementing binary neural network with (+1, -1) weights and (+1, 0) neurons.
Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018
Proceedings of the 2018 IEEE Asia Pacific Conference on Circuits and Systems, 2018