Fan Zhang

Orcid: 0000-0002-6823-2700

Affiliations:
  • Arizona State University, School of Electrical, Computer and Energy Engineering, Tempe, AZ, USA
  • Binghamton University, NY, USA


According to our database1, Fan Zhang authored at least 22 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
On-Device Continual Learning With STT-Assisted-SOT MRAM-Based In-Memory Computing.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., August, 2024

A 65-nm RRAM Compute-in-Memory Macro for Genome Processing.
IEEE J. Solid State Circuits, July, 2024

Efficient Memory Integration: MRAM-SRAM Hybrid Accelerator for Sparse On-Device Learning.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

Hyb-Learn: A Framework for On-Device Self-Supervised Continual Learning with Hybrid RRAM/SRAM Memory.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

SP-IMC: A Sparsity Aware In-Memory-Computing Macro in 28nm CMOS with Configurable Sparse Representation for Highly Sparse DNN Workloads.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2024

2023
Aligner-D: Leveraging In-DRAM Computing to Accelerate DNA Short Read Alignment.
IEEE J. Emerg. Sel. Topics Circuits Syst., March, 2023

Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing.
CoRR, 2023

Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction.
Proceedings of the International Conference on Machine Learning, 2023

A 65nm RRAM Compute-in-Memory Macro for Genome Sequencing Alignment.
Proceedings of the 49th IEEE European Solid State Circuits Conference, 2023

DSPIMM: A Fully Digital SParse In-Memory Matrix Vector Multiplier for Communication Applications.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
MnM: A Fast and Efficient Min/Max Searching in MRAM.
Proceedings of the GLSVLSI '22: Great Lakes Symposium on VLSI 2022, Irvine CA USA, June 6, 2022

A 1.23-GHz 16-kb Programmable and Generic Processing-in-SRAM Accelerator in 65nm.
Proceedings of the 48th IEEE European Solid State Circuits Conference, 2022

XST: A Crossbar Column-wise Sparse Training for Efficient Continual Learning.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

XMA: a crossbar-aware multi-task adaption framework via shift-based mask learning method.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

XBM: A Crossbar Column-wise Binary Mask Learning Method for Efficient Multiple Task Adaption.
Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

Efficient Multi-task Adaption for Crossbar-based In-Memory Computing.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021
PIM-Quantifier: A Processing-in-Memory Platform for mRNA Quantification.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Max-PIM: Fast and Efficient Max/Min Searching in DRAM.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020
Mitigate Parasitic Resistance in Resistive Crossbar-based Convolutional Neural Networks.
ACM J. Emerg. Technol. Comput. Syst., 2020

CCCS: Customized SPICE-level Crossbar-array Circuit Simulator for In-Memory Computing.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

Defects Mitigation in Resistive Crossbars for Analog Vector Matrix Multiplication.
Proceedings of the 25th Asia and South Pacific Design Automation Conference, 2020

2018
Memristor-based Deep Convolution Neural Network: A Case Study.
CoRR, 2018


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