Jungwook Choi

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 98

Top Venues

Publications

Janghwan Lee, Seongmin Park, Sukjin Hong, Minsoo Kim, Du-Seong Chang, Jungwook Choi
Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment. ACL (1) (2024)
Seongmin Park, Hyungmin Kim, Hyunhak Kim, Jungwook Choi
Pruning With Scaled Policy Constraints for Light-Weight Reinforcement Learning. IEEE Access 12 (2024)
Minjae Lee, Seongmin Park, Hyungmin Kim, Minyong Yoon, Janghwan Lee, Jun Won Choi, Nam Sung Kim, Mingu Kang, Jungwook Choi
SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Driving. HPCA (2024)
Minsoo Kim, Sihwa Lee, Wonyong Sung, Jungwook Choi
RA-LoRA: Rank-Adaptive Parameter-Efficient Fine-Tuning for Accurate 2-bit Quantized Large Language Models. ACL (Findings) (2024)
Youngdeok Hwang, Janghwan Lee, Jiwoong Park, Jieun Lim, Jungwook Choi
Searching Optimal Floating-Point Format for Sub-8-Bit Large Language Model Inference. ICEIC (2024)
Yerin Lee, Jimin Jeon, Jungwook Choi, Soobum Park, Bang Chul Jung, Howon Lee
P²URE: Proactive and Probabilistic Uncovered Neighbor-Aware Relay-Selection Method in Multi-Hop FANETs. IEEE Access 12 (2024)
Jinwoo Jeong, Byungmin Ahn, Dongmin Shin, Jungwook Choi
Lightweight Error Correction for In-Storage Acceleration of Large Language Model Inference. ICEIC (2024)
Janghwan Lee, Seongmin Park, Sukjin Hong, Minsoo Kim, Du-Seong Chang, Jungwook Choi
Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment. CoRR (2024)
Minyong Yoon, Jungwook Choi
Architecture-Aware Optimization of Layer Fusion for Latency-Optimal CNN Inference. AICAS (2023)
Minsoo Kim, Kyuhong Shim, Seongmin Park, Wonyong Sung, Jungwook Choi
Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers. EACL (2023)
Janghyeon Kim, Janghwan Lee, Jungwook Choi, JeongHo Han, Sangheon Lee
Range-Invariant Approximation of Non-Linear Operations for Efficient BERT Fine-Tuning. DAC (2023)
Kyuhong Shim, Jungwook Choi, Wonyong Sung
Exploring Attention Map Reuse for Efficient Transformer Neural Networks. CoRR (2023)
Jong Wook Bae, Jungho Kim, Junyong Yun, Changwon Kang, Jeongseon Choi, Chanhyeok Kim, Junho Lee, Jungwook Choi, Jun Won Choi
SiT Dataset: Socially Interactive Pedestrian Trajectory Dataset for Social Navigation Robots. NeurIPS (2023)
Woong Son, Jungwook Choi, Soobum Park, Howon Lee, Bang Chul Jung
A Time Synchronization Protocol for Barrage Relay Networks. Sensors 23 (5) (2023)
Minjae Lee, Hyungmin Kim, Seongmin Park, Minyong Yoon, Janghwan Lee, Junwon Choi, Mingu Kang, Jungwook Choi
PillarAcc: Sparse PointPillars Accelerator for Real-Time Point Cloud 3D Object Detection on Edge Devices. CoRR (2023)
Ki-Hun Lee, Howon Lee, Jungwook Choi, Soobum Park, Bang Chul Jung
Distributed Space-Time Block Coding for Barrage Relay Networks. MILCOM (2023)
Janghwan Lee, Minsoo Kim, Seungcheol Baek, Seok Joong Hwang, Wonyong Sung, Jungwook Choi
Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization. EMNLP (2023)
Minsoo Kim, Kyuhong Shim, Seongmin Park, Wonyong Sung, Jungwook Choi
Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers. CoRR (2023)
Janghwan Lee, Youngdeok Hwang, Jungwook Choi
Finding Optimal Numerical Format for Sub-8-Bit Post-Training Quantization of Vision Transformers. ICASSP (2023)
Minsoo Kim, Sihwa Lee, Janghwan Lee, Sukjin Hong, Du-Seong Chang, Wonyong Sung, Jungwook Choi
Token-Scaled Logit Distillation for Ternary Weight Generative Language Models. CoRR (2023)
Janghwan Lee, Minsoo Kim, Seungcheol Baek, Seok Joong Hwang, Wonyong Sung, Jungwook Choi
Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization. CoRR (2023)
Minsoo Kim, Sihwa Lee, Janghwan Lee, Sukjin Hong, Du-Seong Chang, Wonyong Sung, Jungwook Choi
Token-Scaled Logit Distillation for Ternary Weight Generative Language Models. NeurIPS (2023)
Seokhyeon Choi, Kyuhong Shim, Jungwook Choi, Wonyong Sung, Byonghyo Shim
Optimization of General Matrix Multiply Library for Ternary Weight for Fast DNN Inference. J. Signal Process. Syst. 94 (10) (2022)
Junkyeong Choi, Hyucksung Kwon, Woongkyu Lee, Jieun Lim, Jungwook Choi
Understanding and Optimizing INT4 Convolution for Accelerated DNN Inference on Tensor Cores. SiPS (2022)
Minjae Lee, Zhongfeng Zhang, Seungwon Choi, Jungwook Choi
Minimizing Global Buffer Access in a Deep Learning Accelerator Using a Local Register File with a Rearranged Computational Sequence. Sensors 22 (8) (2022)
Joonsang Yu, Junki Park, Seongmin Park, Minsoo Kim, Sihwa Lee, Dong Hyun Lee, Jungwook Choi
NN-LUT: neural approximation of non-linear operations for efficient transformer inference. DAC (2022)
Minsoo Kim, Sihwa Lee, Sukjin Hong, Du-Seong Chang, Jungwook Choi
Understanding and Improving Knowledge Distillation for Quantization Aware Training of Large Transformer Encoders. EMNLP (2022)
Kyuhong Shim, Jungwook Choi, Wonyong Sung
Understanding the Role of Self Attention for Efficient Speech Recognition. ICLR (2022)
Janghwan Lee, Jungwook Choi
Optimizing Exponent Bias for Sub-8bit Floating-Point Inference of Fine-tuned Transformers. AICAS (2022)
Seongmin Park, Wonyong Sung, Jungwook Choi
Regularizing Activation Distribution for Ultra Low-bit Quantization-Aware Training of MobileNets. SiPS (2022)
Junkyeong Choi, Hyucksung Kwon, Woongkyu Lee, Jungwook Choi, Jieun Lim
Learning from distinctive candidates to optimize reduced-precision convolution program on tensor cores. CoRR (2022)
Minsoo Kim, Sihwa Lee, Sukjin Hong, Du-Seong Chang, Jungwook Choi
Understanding and Improving Knowledge Distillation for Quantization-Aware Training of Large Transformer Encoders. CoRR (2022)
Moonseok Jang, Kexin Wang, Sangjin Lee, Hyeonggyu Jeong, In-Yeong Song, Yong Ho Song, Jungwook Choi
Achieving low write latency through new stealth program operation supporting early write completion in NAND flash memory. J. Syst. Archit. 133 (2022)
Seongmin Park, Beomseok Kwon, Jieun Lim, Kyuyoung Sim, Taeho Kim, Jungwook Choi
Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization. CoRR (2022)
Jeongmin Lee, Moonseok Jang, Wang Kexin, In-Yeong Song, Hyeonggyu Jeong, Jinwoo Jeong, Yong Ho Song, Jungwook Choi
Improving NVM Lifetime Using Task Stack Migration on Low-End MCU-Based Devices. IEEE Access 10 (2022)
Sae Kyu Lee, Ankur Agrawal, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matthew Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, Monodeep Kar, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Kyu-Hyoun Kim, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
A 7-nm Four-Core Mixed-Precision AI Chip With 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling. IEEE J. Solid State Circuits 57 (1) (2022)
Muhammad Shafique, Mahum Naseer, Theocharis Theocharides, Christos Kyrkou, Onur Mutlu, Lois Orosa, Jungwook Choi
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead. CoRR (2021)
Kyuhong Shim, Iksoo Choi, Wonyong Sung, Jungwook Choi
Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling. CoRR (2021)
Hyun Jae Park, Cheol-woong Lee, Taeyoung Shin, Byeong-Hee Roh, Soo Bum Park, Jungwook Choi
Implementation of Embedded Testbeds Using USRP and GNU-Radio for Performance Measurement and Analysis of PPS and PCO-Based Time Synchronizations. Int. J. Interdiscip. Telecommun. Netw. 13 (1) (2021)
Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks. AAAI (2021)
Ankur Agrawal, Sae Kyu Lee, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matt Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Monodeep Kar, Kyu-Hyoun Kim, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan
A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling. ISSCC (2021)
Seokhyeon Choi, Kyuhong Shim, Jungwook Choi, Wonyong Sung, Byonghyo Shim
TernGEMM: GEneral Matrix Multiply Library with Ternary Weights for Fast DNN Inference. SiPS (2021)
Joonyong Jeong, Gyeongyong Lee, Jungkeol Lee, Jungwook Choi, Yong Ho Song
Buffer Management With Append-Only Data Isolation for Improving SSD Performance. IEEE Access 9 (2021)
Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan
RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA (2021)
Woongkyu Lee, Hyucksung Kwon, Jungwook Choi
Thermal Face Detection for High-Speed AI Thermometer. IC-NIDC (2021)
Kyuhong Shim, Iksoo Choi, Wonyong Sung, Jungwook Choi
Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling. ISOCC (2021)
Jinwon Joo, Minyong Yoon, Jungwook Choi, Mingu Kang, JongGeon Lee, Jinin So, IlKwon Yun, Yongsuk Kwon, KyungSoo Kim
Understanding and Reducing Weight-Load Overhead of Systolic Deep Learning Accelerators. ISOCC (2021)
Gyeongyong Lee, Jaewook Kwak, Joonyong Jeong, Daeyong Lee, Moonseok Jang, Jungwook Choi, Yong Ho Song
Internal Task-Aware Command Scheduling to Improve Read Performance of Embedded Flash Storage Systems. IEEE Access 9 (2021)
Hyunwoo Kim, Jeonghoon Kim, Jungwook Choi, Jungkeol Lee, Yong Ho Song
Binarized Encoder-Decoder Network and Binarized Deconvolution Engine for Semantic Segmentation. IEEE Access 9 (2021)
Joonsang Yu, Junki Park, Seongmin Park, Minsoo Kim, Sihwa Lee, Dong Hyun Lee, Jungwook Choi
NN-LUT: Neural Approximation of Non-Linear Operations for Efficient Transformer Inference. CoRR (2021)
Youngseok Kim, Seyoung Kim, Chun-Chen Yeh, Vijay Narayanan, Jungwook Choi
Hardware and Software Co-optimization for the Initialization Failure of the ReRAM-based Cross-bar Array. ACM J. Emerg. Technol. Comput. Syst. 16 (4) (2020)
Theocharis Theocharides, Muhammad Shafique, Jungwook Choi, Onur Mutlu
Guest Editorial: Robust Resource-Constrained Systems for Machine Learning. IEEE Des. Test 37 (2) (2020)
Swagath Venkataramani, Xiao Sun, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Mingu Kang, Ankur Agarwal, Jinwook Oh, Shubham Jain, Tina Babinsky, Nianzheng Cao, Thomas W. Fox, Bruce M. Fleischer, George Gristede, Michael Guillorn, Howard Haynie, Hiroshi Inoue, Kazuaki Ishizaki, Michael J. Klaiber, Shih-Hsien Lo, Gary W. Maier, Silvia M. Mueller, Michael Scheuermann, Eri Ogawa, Marcel Schaal, Mauricio J. Serrano, Joel Silberman, Christos Vezyrtzis, Wei Wang, Fanchieh Yee, Jintao Zhang, Matthew M. Ziegler, Ching Zhou, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Vijayalakshmi Srinivasan, Leland Chang, Kailash Gopalakrishnan
Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE 108 (12) (2020)
Jinwook Oh, Sae Kyu Lee, Mingu Kang, Matthew M. Ziegler, Joel Silberman, Ankur Agrawal, Swagath Venkataramani, Bruce M. Fleischer, Michael Guillorn, Jungwook Choi, Wei Wang, Silvia M. Mueller, Shimon Ben-Yehuda, James Bonanno, Nianzheng Cao, Robert Casatuta, Chia-Yu Chen, Matt Cohen, Ophir Erez, Thomas W. Fox, George Gristede, Howard Haynie, Vicktoria Ivanov, Siyu Koswatta, Shih-Hsien Lo, Martin Lutz, Gary W. Maier, Alex Mesh, Yevgeny Nustov, Scot Rider, Marcel Schaal, Michael Scheuermann, Xiao Sun, Naigang Wang, Fanchieh Yee, Ching Zhou, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference. VLSI Circuits (2020)
Daeyong Lee, Jaewook Kwak, Gyeongyong Lee, Moonseok Jang, Joonyong Jeong, Wang Kexin, Jungwook Choi, Yong Ho Song
Improving Write Performance Through Reliable Asynchronous Operation in Physically-Addressable SSD. IEEE Access 8 (2020)
Joonyong Jeong, Jaewook Kwak, Daeyong Lee, Seungdo Choi, Jungkeol Lee, Jungwook Choi, Yong Ho Song
Level Aware Data Placement Technique for Hybrid NAND Flash Storage of Log-Structured Merge-Tree Based Key-Value Store System. IEEE Access 8 (2020)
Junki Park, Hyunsung Yoon, Daehyun Ahn, Jungwook Choi, Jae-Joon Kim
OPTIMUS: OPTImized matrix MUltiplication Structure for Transformer neural network accelerator. MLSys (2020)
Jaewook Kwak, Jungkeol Lee, Daeyong Lee, Joonyong Jeong, Gyeongyong Lee, Jungwook Choi, Yong Ho Song
GALRU: A Group-Aware Buffer Management Scheme for Flash Storage Systems. IEEE Access 8 (2020)
Youngseok Kim, Seyoung Kim, Chun-Chen Yeh, Vijay Narayanan, Jungwook Choi
Hardware and software co-optimization for the initialization failure of the ReRAM based cross-bar array. CoRR (2020)
Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks. CoRR (2020)
Muhammad Shafique, Mahum Naseer, Theocharis Theocharides, Christos Kyrkou, Onur Mutlu, Lois Orosa, Jungwook Choi
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead. IEEE Des. Test 37 (2) (2020)
Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. CoRR (2019)
Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang
BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. DAC (2019)
Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Zhuo Wang, Pierce Chuang
Accurate and Efficient 2-bit Quantized Neural Networks. MLSys (2019)
Ankur Agrawal, Bruce M. Fleischer, Silvia M. Mueller, Xiao Sun, Naigang Wang, Jungwook Choi, Kailash Gopalakrishnan
DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference. ARITH (2019)
Hoyong Choi, Jihwan Bang, Namjo Ahn, Jinhwan Jung, Jungwook Choi, Soobum Park, Yung Yi
CH-MAC: A Cluster-based, Hybrid TDMA MAC Protocol over Wireless Ad-hoc Networks. MILCOM (2019)
Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Swagath Venkataramani, Jungwook Choi, Wei Wang, Vijayalakshmi Srinivasan, Moriyoshi Ohara, Kailash Gopalakrishnan
A Compiler for Deep Neural Network Accelerators to Generate Optimized Code for a Wide Range of Data Parameters from a Hand-crafted Computation Kernel. COOL CHIPS (2019)
Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung
Workload-aware Automatic Parallelization for Multi-GPU DNN Training. ICASSP (2019)
Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan
Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. HiPC (2019)
Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Wei Wang, Jintao Zhang, Marcel Schaal, Mauricio J. Serrano, Kazuaki Ishizaki, Hiroshi Inoue, Eri Ogawa, Moriyoshi Ohara, Leland Chang, Kailash Gopalakrishnan
DeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator. IEEE Micro 39 (5) (2019)
Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks. NeurIPS (2019)
Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. ICLR (Poster) (2019)
Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators. IISWC (2019)
Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. AAAI (2018)
Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan
Training Deep Neural Networks with 8-bit Floating Point Numbers. NeurIPS (2018)
Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Pierce Chuang, Leland Chang
Compensated-DNN: energy efficient low-precision deep neural networks by compensating quantization errors. DAC (2018)
Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh R. Shanbhag
True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization. ICASSP (2018)
Jungwook Choi, Pierce I-Jen Chuang, Zhuo Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
Bridging the Accuracy Gap for 2-bit Quantized Neural Networks (QNN). CoRR (2018)
Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Vijayalakshmi Srinivasan, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan
A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference. VLSI Circuits (2018)
Prakalp Srivastava, Mingu Kang, Sujan K. Gonugondla, Sungmin Lim, Jungwook Choi, Vikram S. Adve, Nam Sung Kim, Naresh R. Shanbhag
PROMISE: An End-to-End Design of a Programmable Mixed-Signal Accelerator for Machine-Learning Algorithms. ISCA (2018)
Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan
Training Deep Neural Networks with 8-bit Floating Point Numbers. CoRR (2018)
Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
PACT: Parameterized Clipping Activation for Quantized Neural Networks. CoRR (2018)
Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang
Taming the beast: Programming Peta-FLOP class Deep Learning Systems. ISLPED (2018)
Vijayalakshmi Srinivasan, Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan
Across the Stack Opportunities for Deep Learning Acceleration. ISLPED (2018)
Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani
Exploiting approximate computing for deep learning acceleration. DATE (2018)
Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung
Workload-aware Automatic Parallelization for Multi-GPU DNN Training. CoRR (2018)
Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang
Accelerator Design for Deep Learning Training: Extended Abstract: Invited. DAC (2017)
Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang
POSTER: Design Space Exploration for Performance Optimization of Deep Neural Networks on Shared Memory Accelerators. PACT (2017)
Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. CoRR (2017)
Tianqi Gao, Jungwook Choi, Shang-nien Tsai, Rob A. Rutenbar
Toward a pixel-parallel architecture for graph cuts inference on FPGA. FPL (2017)
Jungwook Choi, Ameya D. Patil, Rob A. Rutenbar, Naresh R. Shanbhag
Analysis of error resiliency of belief propagation in computer vision. ICASSP (2016)
Eric P. Kim, Jungwook Choi, Naresh R. Shanbhag, Rob A. Rutenbar
Error Resilient and Energy Efficient MRF Message-Passing-Based Stereo Matching. IEEE Trans. Very Large Scale Integr. Syst. 24 (3) (2016)
Ankur Agrawal, Jungwook Choi, Kailash Gopalakrishnan, Suyog Gupta, Ravi Nair, Jinwook Oh, Daniel A. Prener, Sunil Shukla, Vijayalakshmi Srinivasan, Zehra Sura
Approximate computing: Challenges and opportunities. ICRC (2016)
Jungwook Choi, Rob A. Rutenbar
Video-Rate Stereo Matching Using Markov Random Field TRW-S Inference on a Hybrid CPU+FPGA Computing Platform. IEEE Trans. Circuits Syst. Video Technol. 26 (2) (2016)
Jungwook Choi, Rob A. Rutenbar
Configurable and scalable belief propagation accelerator for computer vision. FPL (2016)
Jinwook Oh, Jungwook Choi, Guilherme C. Januario, Kailash Gopalakrishnan
Energy-Efficient Simultaneous Localization and Mapping via Compounded Approximate Computing. SiPS (2016)
Dae-Young Kim, Zilong Jin, Jungwook Choi, Ben Lee, Jinsung Cho
Transmission Power Control with the Guaranteed Communication Reliability in WSN. Int. J. Distributed Sens. Networks 11 (2015)
Skand Hurkat, Jungwook Choi, Eriko Nurvitadhi, José F. Martínez, Rob A. Rutenbar
Fast hierarchical implementation of sequential tree-reweighted belief propagation for probabilistic inference. FPL (2015)
Eric P. Kim, Jungwook Choi, Naresh R. Shanbhag, Rob A. Rutenbar
A robust message passing based stereo matching kernel via system-level error resiliency. ICASSP (2014)
Jungwook Choi, Rob A. Rutenbar
Video-rate stereo matching using markov random field TRW-S inference on a hybrid CPU+FPGA computing platform. FPGA (2013)

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Publication Activity (10 Years)

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Jungwook Choi