2025

1. H. Shin, J. Kung, "FlexENM: A flexible encrypting-near-memory with refresh-less eDRAM-based multi-mode AES," accepted for publication at Design, Automation and Test in Europe Conference (DATE), March 2025.

2. G. Kang*, D. Park*, H. Lee, S. Jung, J. Park, J. G. Min, Y. Lee, J. Kung, "RISC-V driven orchestration of vector processing units and eFlash compute-in-memory arrays for fast and accurate keyword spotting," accepted for publication at IEEE/ACM Asia and South Pacific Design Automation Conference (ASPDAC), January 2025. *Equally Contributed Authors

2024

1. S. Hwang, S. Lee, D. Park, D. Lee, J. Kung, "SpikedAttention: Training-free and fully spike-driven transformer-to-SNN conversion with winner-oriented spike shift for softmax operation," accepted for publication at the Annual Conference on Neural Information Processing Systems (NeurIPS), December 2024.

2. D.-G. Choi, J. Lee, J. Koo, W. K. Han, D. Park, J. Kung, J. Lee, J.-H. Yoon, "A 65nm 687.5-TOPS/W drive strength-based SRAM compute-in-memory macro with adaptive dynamic range for edge AI applications," accepted for publication at IEEE Asian Solid-State Circuits Conference (A-SSCC), November 2024.

3. J. Koo*, D. Park*, S. Jung, J. Kung, "OPAL: Outlier-preserved microscaling quantization accelerator for generative large language models," IEEE/ACM Design Automation Conference (DAC), June 2024. *Equally Contributed Authors

4. J. Lee, D. Lee, J. Kung, "A ready-to-use RTL generator for systolic tensor arrays and analysis using open-source EDA tools," IEEE International Symposium on Circuits and Systems (ISCAS), May 2024.

5. J. Wie, S. Jung, T. Seol, G. Kim, S. Lee, H. Jang, S. Kim, Y. Shin, J. E. Jang, J. Kung, A. K. George, J. Lee, "A 3.3-to-11V-supply-range 10μW/Ch arbitrary-waveform-capable neural stimulator with output-adaptive-self-bias and supply-tracking schemes in 0.18μm standard CMOS," IEEE Custom Integrated Circuits Conference (CICC), April 2024.

6. J. Kim, S. Oh, J. Kung, Y. Kim, S. Lee, "NDPipe: exploiting near-data processing for scalable inference and continuous training in photo storage," ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), April 2024.

7. S. Jeong, J. Lee, J. Kung, "A full SW-HW demonstration of GEMM accelerators with RISC-V instruction extensions," IEEE/IEIE International Conference on Electronics, Information, and Communication (ICEIC), January 2024.

2025

1. S.-H. Noh, S. Lee, B. Shin, S. Park, Y. Jang, J. Kung, "All-rounder: A flexible AI accelerator with diverse data format support and morphable structure for multi-DNN processing," under revision at IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

2024

2. S. Jung, J. Lee, D. Park, Y. Lee, J.-H. Yoon, J. Kung, "A dual-precision and low-power CNN inference engine using a heterogeneous processing-in-memory architecture," IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), May 2024.

3. S. Hwang and J. Kung, "One-Spike SNN: single-spike phase coding with base manipulation for ANN-to-SNN conversion loss minimization," IEEE Transactions on Emerging Topics in Computing (TETC), April 2024.

4. M. Bodenham and J. Kung, "Skipformer: Evolving Beyond Blocks for Extensively Searching On-Device Language Models with Learnable Attention Window," IEEE Access, September 2024.

1. Amit R. Trivedi, Jaeha Kung, and Jong Hwan Ko, “Architectures for self-powered edge intelligence,” in Handbook of Computer Architecture, Springer, 2022.