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[105]
Y. Liu, Z. Jing, Z. Liu, C. Yip, Z. Zong and H. C. Luong

“A 74GHz-80GHz 1.2GHz/µs-Slope 20.9mW FMCW Synthesizer with TDC-Gain-Independent Loop-Bandwidth Employing a TDC-Offset Free Type-II Digital PLL and a Linearized Hybrid-Tuning DCO”, in IEEE Radio Frequency Integrated Circuits Symposium (RFIC), June 2024.

[104]
Y. Liu, Z. Jing, Z. Liu, W. Yang, C. Yip, L. Wu and H. C. Luong

“A 4.25GHz-8.45GHz 67%-Chirp-Fractional-Bandwidth -121.5dBc/Hz PN@1MHz 88fs-Jitter FMCW Synthesizer with Bandwidth-Boosting and Phase-Noise-Cancellation Techniques”, in IEEE Radio Frequency Integrated Circuits Symposium (RFIC), June 2024.

[103]
Y. Lu, S. Liu, Q. Zhang, and Z. Xie

RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model,” in 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC), 2024.

[101]
Z. Rong, L. Zhang, and M. Chan

Generic Memory Modeling with Recurrent Neural Network”, in 2022 10th International Symposium on Next-Generation Electronics (ISNE), 2023, pp. 1–3.

[100]
Z. Xie, T. Zhang, and Y. Peng

Security and Reliability Challenges in Machine Learning for EDA: Latest Advances,” in 2023 24th International Symposium on Quality Electronic Design (ISQED), 2023, pp. 1–6.

[99]
J. He, Y. Huang, M. Lastras, T. T. Ye, C.-Y. Tsui, and K.-T. Cheng

“RVComp: Analog Variation Compensation for RRAM-based In-Memory Computing,” in 2023 28th Asia and South Pacific Design Automation Conference (ASP-DAC), 2023, pp. 1–6.

[98]
T. Liu and E. F. Young

Rethinking AIG Resynthesis in Parallel,” in 2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, pp. 1–6.

[97]
R. Mao, X. Sheng, C. Graves, C. Xu, and C. Li

ReRAM-based graph attention network with node-centric edge searching and hamming similarity,” in 2023 60th ACM/IEEE Design Automation Confer- ence (DAC), 2023, pp. 1–6.

[96]
A. Ahmad, Z. Xie, and W. Zhang

PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search,” in 2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, pp. 1–6.

[95]
X. Chen, R. Pan, X. Wang, F. Tian, and C.-Y. Tsui

Late Breaking Results: Weight Decay is ALL You Need for Neural Network Sparsification,” in 2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, pp. 1–2.

[94]
L. Liu, S. Kumar, S. Thomann, H. Amrouch, and X. S. Hu

Compact and High-Performance TCAM Based on Scaled Double-Gate FeFETs,” in 2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, pp. 1–6.

[93]
J. Chen, F. Tu, K. Shao, et al.

AutoDCIM: An Automated Digital CIM Compiler,” in 2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, pp. 1–6.

[92]
H. Yuan, Y. Char, S. Dai, et al.

 “Design and demonstration of Cu/Al2O3 /Cu RRAM with complementary resistance switching characteristic,” in 2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM), 2023, pp. 1–3.

[91]
S.-Q. Dai, C. J. Estrada, A. Xiong, et al.

A Multiple Junction Photonic Demodulator with Low Power Consumption for Time-of-Flight Application,” in 2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM), 2023, pp. 1–3.

[90]
T. Srimani, R. M. Radway, J. Kim, et al.

Ultra-Dense 3D Physical Design Unlocks New Architectural Design Points with Large Benefits,” in 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023, pp. 1–6.

[89]
L. Chen, X. Li, F. Jiang, C. Li, and J. Xu

Smart Knowledge Transfer-based Runtime Power Management,” in 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023, pp. 1–6.

[88]
Y. Zhang, S. R. Sathi, Z. Kou, S. Sinha, and W. Zhang

 “Tensor-Product-Based Accelerator for Area-efficient and Scalable Number Theoretic Transform,” in 2023 IEEE 31st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2023, pp. 174–183.

[87]
J. Wu, J. Zhou, Y. Gao, Y. Ding, N. Wong, and H. K.-H. So

MSD: Mixing Signed Digit Representations for Hardware-efficient DNN Acceleration on FPGA with Heterogeneous Resources,” in 2023 IEEE 31st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2023, pp. 94–104.

[86]
Y. Ding, J. Wu, Y. Gao, M. Wang, and H. K.-H. So

Model-Platform Optimized Deep Neural Network Accelerator Generation through Mixed-Integer Geometric Programming,” in 2023 IEEE 31st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2023, pp. 83–93.