Publications

2024

• Sungyoun Hwang*†, Hyelin Seok*†, and Yongtae Kim, "Design of an Approximate 4-2 Compressor with Error Recovery for Efficient Approximate Multiplication," Journal of Semiconductor Technology and Science, to appear. (†Equal Contributions)

• Dong-Hee Yoon, Hyoju Seo*, Jungwon Lee*, and Yongtae Kim, "Online Electric Vehicle Charging Strategy in Residential Areas with Limited Power Supply," IEEE Transactions on Smart Grid, vol. 15, no. 3, pp. 3141 - 3151, May 2024.

• Sanghyeon Lee, Leanghok Hour, Yongtae Kim, and Youngsun Han, "ReQUSA: A Novel ReRAM-based Hardware Accelerator Architecture for High-Speed Quantum Computer Simulation," Physica Scripta, vol. 99, no. 3, pp. 1-15, Mar. 2024.

2023

• Hyoju Seo* and Yongtae Kim, "A Low Latency Approximate Adder Design based on Dual Sub-Adders with Error Recovery," IEEE Transactions on Emerging Topics in Computing, vol. 11, no. 3, pp. 811-816, July-Sept. 2023.

• Hyoju Seo*, Hyelin Seok*, Jungwon Lee*, Youngsun Han, and Yongtae Kim, "Design of an Approximate Adder based on Modified Full Adder and Nonzero Truncation for Machine Learning," Journal of Semiconductor Technology and Science, vol. 23, no. 2, pp. 138-148, Apr. 2023.

2022

• Hyelin Seok*, Hyoju Seo*, Jungwon Lee*, and Yongtae Kim, "Design Optimization of a 4-2 Compressor for Low-Cost Approximate Multipliers," IEIE Transactions on Smart Computing and Processing, vol. 11, no. 6, pp. 455-461, Dec. 2022. (Haedong Best Paper Award)

• Minseob Shim, Junwon Jeong, Junyoung Song, Yongtae Kim, and Woong Choi, "Segmented Match-Line and Charge-Sharing Based Low-Cost TCAM," IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 69, no. 12, pp. 5104-5108, Dec. 2022.

• Junhyuk Baik* and Yongtae Kim, "A High-Throughput and Energy-Efficient SHA-256 Design using Approximate Arithmetic," IEIE Transactions on Smart Computing and Processing, vol. 11, no. 5, pp. 385-391, Oct. 2022.

• Donghui Lee*, Myeongjin Kwak*, Jungwon Lee*, Beomjun Kim*, and Yongtae Kim, "A Light-Weight AES Design using LFSR-based S-Box for IoT Applications," IEIE Transactions on Smart Computing and Processing, vol. 11, no. 2, pp. 140-148, Apr. 2022. (Haedong Best Paper Award)

• Beomjun Kim*, Yongtae Kim, Prashant Nair, and Seokin Hong "Exploiting Data Compression for Adaptive Block Placement in Hybrid Cache," Electronics, vol. 11, no. 2, pp. 240:1-240:18, Jan. 2022.

2021

• Woong Choi, Minseob Shim, Hyelin Seok*, and Yongtae Kim, "DCPA: Approximate Adder Design Exploiting Dual Carry Prediction," IEICE Electronics Express, vol. 18, no. 23, pp. 1-4, Dec. 2021.

• Yoon Seok Yang and Yongtae Kim, “Low-Power Cross-Layer Error Management Using MIMO-LDPC Iterative Decoding for Video Processing,” IEEE Access, vol. 9, pp. 133062-133075, Sept. 2021.

• Hyelin Seok*, Hyoju Seo*, Jungwon Lee*, and Yongtae Kim, “COREA: Delay- and Energy-Efficient Approximate Adder Using Effective Carry Speculation,” Electronics, vol. 10, no. 18, pp. 2234:1-2234:12, Sept. 2021.

• Jungwon Lee*†, Hyoju Seo*†, Hyelin Seok*, and Yongtae Kim, “A Novel Approximate Adder Design using Error Reduced Carry Prediction and Constant Truncation,” IEEE Access, vol 9. pp. 119939-119953, Aug. 2021. (†Equal Contributions)

• Hyoju Seo*, Jungwon Lee*, Donghui Lee*, Beomjun Kim*, and Yongtae Kim, “Design and Analysis of a Low-Cost Approximate Adder with OR and Zero Truncation,” IEIE Transactions on Smart Computing and Processing, vol. 10, no. 4, pp. 309-314, Aug. 2021.

• Youngsun Han, Sanghyeon Lee, Byung Wook Kim, and Yongtae Kim, “Resource-Optimized Design of Bit-Shuffle Block Coding for MIMO-VLC,” IEEE Access, vol. 9, pp. 97675-97685, July 2021.

2020

• Youngsun Han, Dongmin Kim, and Yongtae Kim, “A Novel ReRAM-based Architecture of Field Sequential Color Driver for High-Resolution LCoS Displays,” IEEE Access, vol. 8, pp. 223385 - 223395, Dec. 2020.

• Jungwon Lee*, Hyoju Seo*, Yerin Kim*, and Yongtae Kim, “Approximate Adder Design with Simplified Lower-part Approximation,” IEICE Electronics Express, vol. 17, no. 15, pp. 1-3, Aug. 2020. 

• Yoon Seok Yang and Yongtae Kim, “Approximate Digital Leaky Integrate-and-Fire Neurons for Energy Efficient Spiking Neural Networks,” IEIE Transactions on Smart Computing and Processing, vol. 9, no. 3, pp. 252-259, June 2020. 

• Hyoju Seo*, Yoon Seok Yang and Yongtae Kim, “Design and Analysis of an Approximate Adder with Hybrid Error Reduction,” Electronics, vol. 9, no. 3, pp. 471:1-471:13, Mar. 2020. 

2019

• Yongtae Kim, “A Novel Approximate Adder with Enhanced Low-Cost Carry Prediction for Error Tolerant Computing,” IEIE Transactions on Smart Computing and Processing, vol. 8, no. 4, pp. 506-510, Dec. 2019. 

• Junyoung Song, Yongtae Kim, and Chulwoo Kim, “A 9Gb/s/ch Transceiver with Reference-less Data-embedded Pseudo-differential Clock Signaling for Graphics Memory Interfaces,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 12, pp. 1982-1986, Dec. 2019.

• Youngsun Han, Yongtae Kim, and Byung Wook Kim, “Bit-shuffle Coding for Flicker Mitigation in Visible Light Communication,” IEEE Access, vol. 7, pp. 150271-150279, Oct. 2019.  

• Yongtae Kim, “An Accuracy Enhanced Error Tolerant Adder with Carry Prediction for Approximate Computing,” IEIE Transactions on Smart Computing and Processing, vol. 8, no. 4, pp. 324-330, Aug. 2019. 

~2018

• Qian Wang, Yongtae Kim, and Peng Li, “Neuromorphic Processors with Memristive Synapses: Synaptic Crossbar Interface and Architectural Exploration,” ACM Journal on Emerging Technologies in Computing Systems, vol. 12, no. 4, pp. 35:1-35:22, May 2016. 

• Yongtae Kim, Yong Zhang, and Peng Li, “Energy Efficient Approximate Arithmetic for Error Resilient Neuromorphic Computing,” IEEE Transactions on VLSI System, vol. 23, no. 11, pp. 2733-2737, Nov. 2015. 

• Qian Wang, Peng Li, and Yongtae Kim, “A Parallel Digital VLSI Architecture for Integrated Support Vector Machine Training and Classification,” IEEE Transactions on VLSI Systems, vol. 23, no. 8, pp. 1471-1484, Aug. 2015. 

• Yongtae Kim, Yong Zhang, and Peng Li, “A Reconfigurable Digital Neuromorphic Processor with Memristive Synaptic Crossbar for Cognitive Computing,” ACM Journal on Emerging Technologies in Computing Systems, vol. 11, no. 4, pp. 38:1-38:25, Apr. 2015. 

• Minyoung Song, Sunghoon Ahn, Inhwa Jung, Yongtae Kim, and Chulwoo Kim, “Piecewise Linear Modulation Technique for Spread Spectrum Clock Generation,” IEEE Transactions on VLSI Systems, vol. 21, no. 7, pp. 1234-1245, July 2013. 

• Yongtae Kim and Peng Li, “A 0.003-mm2, 0.35-V, 82-pJ/conversion Ultra-Low Power CMOS All Digital Temperature Sensor for On-Die Thermal Management,” Analog Integrated Circuits and Signal Processing, vol. 75, no. 1, pp. 145-156, Apr. 2013. 

• Young-Ho Kwak, Yongtae Kim, and Chulwoo Kim, “A 20 Gb/s Clock and Data Recovery with a Ping-Pong Delay Line for Unlimited Phase Shifting in 65 nm CMOS Process,” IEEE Transactions on Circuits and Systems I, vol. 60, no. 2, pp. 303-313, Feb. 2013. 

• Yongtae Kim and Peng Li, “A 0.38-V Near/Sub-VT Digitally Controlled Low-Dropout Regulator with Enhanced Power Supply Noise Rejection in 90-nm CMOS Process,” IET Circuits, Devices & Systems, vol. 7, no. 1, pp. 31-41, Jan. 2013. 

2024

• Donghui Lee*, Hyoju Seo*, and Yongtae Kim, "Design of an Efficient Parallel Random Number Generator using a Single LFSR for Stochastic Computing," International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Feb. 2024.

• Hyoju Seo*, Hyelin Seok*, Junhyuk Baik*, Donghui Lee*, and Yongtae Kim, "A Cost-Effective Approximate Adder Design for Error Tolerant Applications," International Conference on Green and Human Information Technology (ICGHIT), Jan. 2024. (Best Paper Award)

2023

• Donghui Lee* and Yongtae Kim, "Towards Quantized Stochastic Computing by Leveraging Reduced Precision Binary Numbers through Bit Truncation," IEEE International Conference on Computer Design (ICCD), Nov. 2023.

• Hyoju Seo*, Seokhyeon Lee*, and Yongtae Kim, "Computation Exactness Exploration of Exact Quantum Adders in NISQ," International System-on-Chip Design Conference (ISOCC), Oct. 2023. (Best Paper Award: IEEE CASS Seoul Chapter Award)

• Donghui Lee*, Junhyuk Baik*, and Yongtae Kim, "Enhancing Stochastic Computing using a Novel Hybrid Random Number Generator Integrating LFSR and Halton Sequence," International System-on-Chip Design Conference (ISOCC), Oct. 2023.

• Junhyuk Baik*, Donghui Lee*, and Yongtae Kim, "A Smith-Waterman Hardware Accelerator Design using Sliding Window for Genomic Sequence Alignment," International System-on-Chip Design Conference (ISOCC), Oct. 2023. (Best Paper Award: TechwidU Award)

• Myeongjin Kwak*, Jeonggeun Kim, and Yongtae Kim, "TorchAxf: Enabling Rapid Simulation of Approximate DNN Models using GPU-based Floating-Point Computing Framework," International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), Oct. 2023.  (Acceptance rate: 29%)

2022

• Myeongjin Kwak* and Yongtae Kim, "Do Not Forget: Exploiting Stability-Plasticity Dilemma to Expedite Unsupervised SNN Training for Neuromorphic Processors," IEEE International Conference on Computer Design (ICCD), Oct. 2022. (Acceptance rate: 30.2%, 69 of 228)

• Hyelin Seok*, Hyoju Seo*, Jungwon Lee*, and Yongtae Kim, "A Novel Efficient Approximate Adder Design using Single Input Pair based Computation," International System-on-Chip Design Conference (ISOCC), Oct. 2022. 

• Donghui Lee*, Junhyuk Baik*, and Yongtae Kim, "An Accurate and Efficient Stochastic Computing Adder Exploiting Bit Shuffle Control Scheme," International System-on-Chip Design Conference (ISOCC), Oct. 2022. (Best Paper Award: KETI Award)

• Leanghok Hour, Sanghyeon Lee, Hyoju Seo*, Yongtae Kim, and Youngsun Han, "Partitioning Deep Learning Model to Reduce Memory Latency for Custom Hardware Accelerator," International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC), July 2022.

•  Myeongjin Kwak*, Beomjun Kim*, Donghui Lee*, and Yongtae Kim, "Early Stopping Technique for Unsupervised Spiking Neural Networks," International Conference on Green and Human Information Technology (ICGHIT), Jan. 2022.

2021

• Donghui Lee* and Yongtae Kim, “Design of a Light-Weight Key Scheduler for AES using LFSR for IoT Applications,” IEEE International Conference on Consumer Electronics – Asia (ICCE-Asia), Nov. 2021.

• Myeongjin Kwak*, Hyoju Seo*, and Yongtae Kim, “Precision Exploration of Floating-Point Arithmetic for Spiking Neural Networks,” International System-on-Chip Design Conference (ISOCC), Oct. 2021. (Best Paper Award: KETI Award)

• Hyoju Seo*, Jungwon Lee*, Hyelin Seok*, and Yongtae Kim, “Design of an Accurate Enhanced Imprecise Adder with Half Adder-based Approximation,” International System-on-Chip Design Conference (ISOCC), Oct. 2021.

• Hwiseong Park*, Myeongjin Kwak*, Jungwon Lee*, Hyoju Seo*, and Yongtae Kim, “Unsupervised STDP Learning using Approximate Floating-Point Adder for Energy Efficient Neuromorphic Processors,” International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC), June 2021.

• Myeongjin Kwak*, Jungwon Lee*, Hyoju Seo*, Mingyu Sung*, and Yongtae Kim, “Training and Inference using Approximate Floating-Point Arithmetic for Energy Efficient Spiking Neural Network Processors,” International Conference on Electronics, Information, and Communication (ICEIC), Jan. 2021. (Best Paper Award: Gold Prize, two out of the 251 accepted papers, 0.8%)

2020

• Mingyu Sung* and Yongtae Kim, “Training Spiking Neural Networks with an Adaptive Leaky Integrate-and-Fire Neuron,” IEEE International Conference on Consumer Electronics – Asia (ICCE-Asia), Nov. 2020.

• Hyoju Seo* and Yongtae Kim, “A New Approximate Adder with Duplicate-Constant Scheme for Energy Efficient Applications,” IEEE International Conference on Consumer Electronics – Asia (ICCE-Asia), Nov. 2020. 

• Jungwon Lee*, Hyoju Seo*, Yerin Kim*, and Yongtae Kim, “Design of a Low-Cost Approximate Adder with a Zero Truncation,” International System-on-Chip Design Conference (ISOCC), Oct. 2020.

• Hyoju Seo*, Yoon Seok Yang, and Yongtae Kim, “An Energy-Efficient Imprecise Adder with a Lower-part Constant Approximation,” International System-on-Chip Design Conference (ISOCC), Oct. 2020. (Best Paper Award: IEEE CASS Seoul Chapter Award)

• Yoon Seok Yang and Yongtae Kim, “Recent Trend of Neuromorphic Computing Hardware: Intel’s Neuromorphic System Perspective,” International System-on-Chip Design Conference (ISOCC), Oct. 2020. (Invited)

• Mingyu Sung*, Hyoju Seo*, Yongtae Kim, Dong-Hee Yoon, and Youngsun Han, “Performance Analysis of Bit-Shuffle Coding in Multiple-Input Multiple-Output Visible Light Communication,” International Conference on Green and Human Information Technology (ICGHIT), Feb. 2020. 

2019

• Yongtae Kim, “Digital Leaky Integrate-and-Fire Neuron with Approximate Adders for Spiking Neural Networks,” International Conference on Culture Technology (ICCT), Aug. 2019. 

~2018

• Qian Wang, Yongtae Kim, and Peng Li, “Architectural Design Exploration for Neuromorphic Processors with Memristive Synapses,” IEEE International Conference on Nanotechnology (NANO), Aug. 2014. 

• Yongtae Kim, Yong Zhang, and Peng Li, “An Energy Efficient Approximate Adder with Carry Skip for Error Resilient Neuromorphic VLSI Systems,” IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov. 2013. (Acceptance rate: 26%, 92 of 354)

• Yongtae Kim, Yong Zhang, and Peng Li, “A Brain-Inspired Digital Neuromorphic VLSI Architecture with Memristive Crossbar for Cognitive Computing,” SRC TECHCON, Sept. 2013. 

• Yongtae Kim, Yong Zhang, and Peng Li, “A Brain-Inspired Digital Neuromorphic VLSI Architecture with Memristive Crossbar for Cognitive Computing,” IEEE Texas Workshop on Integrated System Exploration, Mar. 2013. 

• Yongtae Kim, Yong Zhang, and Peng Li, “A Digital Neuromorphic VLSI Architecture with Memristor Crossbar Synaptic Array for Machine Learning,” IEEE International System-on-Chip Conference (SOCC), Sept. 2012. 

• Yongtae Kim and Peng Li, “An On-Chip Variation Tolerant Digital LDO Regulator for Extremely Low Voltage Applications,” SRC TECHCON, Sept. 2012. 

• Yongtae Kim and Peng Li, “An Ultra-Low Voltage Digitally Controlled Low-Dropout Regulator with Digital Background Calibration,” IEEE International Symposium on Quality Electronic Design (ISQED), Mar. 2012. 

• Leyi Yin, Yongtae Kim, and Peng Li, “High Effective-Resolution Built-In Jitter Characterization with Quantization Noise Shaping,” IEEE/ACM Design Automation Conference (DAC), June 2011. (Acceptance rate: 22.6%, 156 of 690)

• Yongtae Kim, Jungyoung Song, Woonhyyung Heo, and Chulwoo Kim, “An Efficient Architecture of Encoder and Decoder for DisplayPort Physical Layer,” IEEE International Conference on Consumer Electronics (ICCE), Jan. 2009. 

• Minyoung Song, Sunghoon Ahn, Inhwa Jung, Yongtae Kim, and Chulwoo Kim, “A 1.5 GHz Spread Spectrum Clock Generator with a 5000ppm Piecewise Linear Modulation,” IEEE Custom Integrated Circuits Conference (CICC), Sept. 2008. 

• Myeongjin Kwak*, Hyoju Seo*, and Yongtae Kim, “Training and Accuracy Analysis of Spiking Neural Network using Floating-Point Formats,” Korea Artificial Intelligence Conference (한국인공지능학술대회), Sept. 2021.

• Hyelin Seok*, Hyoju Seo*, Jungwon Lee*, and Yongtae Kim, “Design of Approximate Adder using AND-based Carry Prediction,” IEIE Summer Annual Conference (대한전자공학회 하계학술대회), Jul. 2021.

• Jungwon Lee*, Jeehyun Woo, Jaeyoung Lee, Hyoju Seo*, and Yongtae Kim, “Low Power Approximate Floating Point Adder Design,” IEIE Summer Annual Conference (대한전자공학회 하계학술대회), Aug. 2020.

• Jungwon Lee*, Seojin Kim, Yubin Kim, Hyoju Seo*, and Yongtae Kim, “Design of Accuracy Improved Approximate Adder,” IEIE Summer Annual Conference (대한전자공학회 하계학술대회), Aug. 2020.

• Dongmin Kim, Yerim Lee, Yongtae Kim, and Youngsun Han, “Design of ReRAM based Field Sequential Color (FSC) Driver for LCoS Display,” IEIE Autumn Annual Conference (대한전자공학회 추계학술대회), Nov. 2019.