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[82]
F. Tian, X. Wang, J. Chen, et al.

 “Binary is All You Need: Ultra-Efficient Arrhythmia Detection with a Binary-Only Compressive System,” in 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2023, pp. 1–5.

[81]
S. Jiang, T.-W. Huang, and T.-Y. Ho

GLARE: Accelerating Sparse DNN Inference Kernels with Global Memory Access Reduction,” in 2023 IEEE High Performance Extreme Computing Conference (HPEC), 2023.

[80]
K. T. Phan, Y. Gao, and H. C. Luong
[79]
K. Toprasertpong, S. Liu, J. Chen, et al.

 “Co-designed Capacitive Coupling-Immune Sensing Scheme for Indium-Tin-Oxide (ITO) 2T Gain Cell Operating at Positive Voltage Below 2 V,” in 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023, pp. 1–2.

[78]
A. Wei, A. Levy, P. Yi, et al.

“PBA: Percentile-Based Level Allocation for Multiple-Bits-Per-Cell RRAM,” in 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2023.

[77]
Q. Zhang, S. Li, G. Zhou, et al.

 “PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions,” in 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2023.

[76]
W. Fang, Y. Lu, S. Liu, et al.

 “MasterRTL: A Pre-Synthesis PPA Estimation Framework for Any RTL Design,” in 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2023.

[75]
S. Zheng, L. Zou, P. XU, S. Liu, B. Yu, and M. Wong

 “Lay-Net: Grafting Netlist Knowledge on Layout- Based Congestion Prediction,” in 2023 IEEE/ACM International Conference On Computer Aided De- sign (ICCAD), 2023.

[74]
C. BAI, X. Wei, Y. Zhuo, et al.

“Klotski: DNN Model Orchestration Framework for Dataflow Architecture Accelerators,” in 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2023.

[73]
Z. Yan, Y. Qin, W. Wen, X. S. Hu, and Y. Shi

Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators through Training with Right-Censored Gaussian Noise,” in 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2023.

[72]
A. F. Laguna, M. M. Sharifi, D. Reis, et al.

“Algorithm/Hardware Co-design for Few-Shot Learning at the Edge,” in 2023 IEEE/ACM International Conference On Computer Aided Design (ICCAD), Invited paper, 2023.

[71]
J. Jiang, X. Chen, and C.-Y. Tsui

“Accelerating Large Kernel Convolutions with Nested Winograd Transformation,” in 2023 IFIP/IEEE 31st International Conference on Very Large Scale Integration (VLSI-SoC), 2023.

[70]
G. A. Eggermann, M. A. Rios, G. Ansaloni, and D. Atienza Alonso

 “A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication,” in 2023 IFIP/IEEE 31st International Conference on Very Large Scale Integration (VLSI-SoC), 2023, p. 6.

[69]
S. Liu, K. Jana, K. Toprasertpong, et al.

“Gain Cell Memory on Logic Platform - Device Guidelines for Oxide Semiconductor Transistor Materials Development,” in 2023 International Electron Devices Meeting (IEDM), 2023.

[68]
S. Zheng, H. Geng, C. Bai, B. Yu, and M. D. F. Wong
[67]
F. Ponzina, M. Rios, A. Levisse, G. Ansaloni, and D. Atienza

 “Overflow-Free Compute Memories for Edge AI Acceleration,” ACM Trans. Embed. Comput. Syst., vol. 22, no. 5s, Sep. 2023.

[66]
B. Shao, T. Wan, F. Liao, et al.

Highly Trustworthy In-Sensor Cryptography for Image Encryption and Authentication,” ACS Nano, vol. 17, no. 11, pp. 10 291–10 299, 2023.

[65]
L. R. Upton, A. Levy, M. D. Scott, et al.

EMBER: A 100 MHz, 0.86 mm2, Multiple-Bits-per-Cell RRAM Macro in 40 nm CMOS with Compact Peripherals and 1.0 pJ/bit Read Circuitry,” in ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC), 2023, pp. 469–472.

[64]
F. Tian, X. Wang, J. Chen, et al.

BIOS: A 40nm Bionic Sensor-defined 0.47pJ/SOP, 268.7TSOPs/W Configurable Spiking Neuron-in-Memory Processor for Wearable Healthcare,” in ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC), 2023, pp. 225–228.

[63]
X. Hou, J. Liu, X. Tang, et al.

MMExit: Enabling Fast and Efficient Multi-modal DNN Inference with Adaptive Network Exits,” in Euro-Par 2023: Parallel Processing, Cham: Springer Nature Switzerland, 2023, pp. 426–440.