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2020 – today
- 2024
[j27]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: 35097-35108 (2024)- [j26]Seongmin Park, Hyungmin Kim, Hyunhak Kim, Jungwook Choi:
Pruning With Scaled Policy Constraints for Light-Weight Reinforcement Learning. IEEE Access 12: 36055-36065 (2024) - [c68]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: 11346-11364 - [c67]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: 15773-15786 - [c66]Dong-eon Won, Yeeun Kim, Janghwan Lee, Minjae Lee, Jonghyun Bae, Jongjoo Park, Jeongyong Song, Jungwook Choi:
ISP2DLA: Automated Deep Learning Accelerator Design for On-Sensor Image Signal Processing. ASAP 2024: 237-238 - [c65]Seongmin Park, Minjae Lee, Junwon Choi, Jungwook Choi:
Selectively Dilated Convolution for Accuracy-Preserving Sparse Pillar-based Embedded 3D Object Detection. CVPR Workshops 2024: 8104-8113 - [c64]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: 1-4 - [c63]Jinwoo Jeong, Byungmin Ahn, Dongmin Shin, Jungwook Choi:
Lightweight Error Correction for In-Storage Acceleration of Large Language Model Inference. ICEIC 2024: 1-4 - [c62]Minsoo Kim, Kyuhong Shim, Jungwook Choi, Simyung Chang:
InfiniPot: Infinite Context Processing on Memory-Constrained LLMs. EMNLP 2024: 16046-16060 - [c61]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: 454-467 - [i22]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 abs/2407.03051 (2024) - [i21]Seongmin Park, Minjae Lee, Junwon Choi, Jungwook Choi:
Selectively Dilated Convolution for Accuracy-Preserving Sparse Pillar-based Embedded 3D Object Detection. CoRR abs/2408.13798 (2024) - [i20]Minsoo Kim, Kyuhong Shim, Jungwook Choi, Simyung Chang:
InfiniPot: Infinite Context Processing on Memory-Constrained LLMs. CoRR abs/2410.01518 (2024) - 2023
- [j25]Woong Son, Jungwook Choi, Soobum Park, Howon Lee, Bang Chul Jung:
A Time Synchronization Protocol for Barrage Relay Networks. Sensors 23(5): 2447 (2023) - [c60]Minyong Yoon, Jungwook Choi:
Architecture-Aware Optimization of Layer Fusion for Latency-Optimal CNN Inference. AICAS 2023: 1-4 - [c59]Janghyeon Kim, Janghwan Lee, Jungwook Choi, JeongHo Han, Sangheon Lee:
Range-Invariant Approximation of Non-Linear Operations for Efficient BERT Fine-Tuning. DAC 2023: 1-6 - [c58]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: 916-929 - [c57]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: 14726-14739 - [c56]Janghwan Lee, Youngdeok Hwang, Jungwook Choi:
Finding Optimal Numerical Format for Sub-8-Bit Post-Training Quantization of Vision Transformers. ICASSP 2023: 1-5 - [c55]Ki-Hun Lee, Howon Lee, Jungwook Choi, Soobum Park, Bang Chul Jung:
Distributed Space-Time Block Coding for Barrage Relay Networks. MILCOM 2023: 292-297 - [c54]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 - [c53]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 - [i19]Kyuhong Shim, Jungwook Choi, Wonyong Sung:
Exploring Attention Map Reuse for Efficient Transformer Neural Networks. CoRR abs/2301.12444 (2023) - [i18]Minsoo Kim, Kyuhong Shim, Seongmin Park, Wonyong Sung, Jungwook Choi:
Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers. CoRR abs/2302.11812 (2023) - [i17]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 abs/2305.07522 (2023) - [i16]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 abs/2308.06744 (2023) - [i15]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 abs/2311.05161 (2023) - 2022
- [j24]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: 125319-125333 (2022) - [j23]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: 102767 (2022) - [j22]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): 182-197 (2022) - [j21]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): 3095 (2022) - [j20]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): 929-943 (2022) - [c52]Janghwan Lee, Jungwook Choi:
Optimizing Exponent Bias for Sub-8bit Floating-Point Inference of Fine-tuned Transformers. AICAS 2022: 98-101 - [c51]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: 577-582 - [c50]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: 6713-6725 - [c49]Kyuhong Shim, Jungwook Choi, Wonyong Sung:
Understanding the Role of Self Attention for Efficient Speech Recognition. ICLR 2022 - [c48]Junkyeong Choi, Hyucksung Kwon, Woongkyu Lee, Jieun Lim, Jungwook Choi:
Understanding and Optimizing INT4 Convolution for Accelerated DNN Inference on Tensor Cores. SiPS 2022: 1-6 - [c47]Seongmin Park, Wonyong Sung, Jungwook Choi:
Regularizing Activation Distribution for Ultra Low-bit Quantization-Aware Training of MobileNets. SiPS 2022: 1-6 - [i14]Junkyeong Choi, Hyucksung Kwon, Woongkyu Lee, Jungwook Choi, Jieun Lim:
Learning from distinctive candidates to optimize reduced-precision convolution program on tensor cores. CoRR abs/2202.06819 (2022) - [i13]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 abs/2211.11014 (2022) - [i12]Seongmin Park, Beomseok Kwon, Jieun Lim, Kyuyoung Sim, Taeho Kim, Jungwook Choi:
Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization. CoRR abs/2212.10878 (2022) - 2021
- [j19]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: 8006-8027 (2021) - [j18]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: 71638-71650 (2021) - [j17]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: 157681-157698 (2021) - [j16]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): 25-35 (2021) - [c46]Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung:
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks. AAAI 2021: 6794-6802 - [c45]Woongkyu Lee, Hyucksung Kwon, Jungwook Choi:
Thermal Face Detection for High-Speed AI Thermometer. IC-NIDC 2021: 163-167 - [c44]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: 153-166 - [c43]Kyuhong Shim, Iksoo Choi, Wonyong Sung, Jungwook Choi:
Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling. ISOCC 2021: 357-358 - [c42]Jinwon Joo, Minyong Yoon, Jungwook Choi, Mingu Kang, Jong-Geon Lee, Jinin So, IlKwon Yun, Yongsuk Kwon, KyungSoo Kim:
Understanding and Reducing Weight-Load Overhead of Systolic Deep Learning Accelerators. ISOCC 2021: 413-414 - [c41]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: 144-146 - [c40]Seokhyeon Choi, Kyuhong Shim, Jungwook Choi, Wonyong Sung, Byonghyo Shim:
TernGEMM: GEneral Matrix Multiply Library with Ternary Weights for Fast DNN Inference. SiPS 2021: 111-116 - [i11]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 abs/2101.02559 (2021) - [i10]Kyuhong Shim, Iksoo Choi, Wonyong Sung, Jungwook Choi:
Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling. CoRR abs/2110.03252 (2021) - [i9]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 abs/2112.02191 (2021) - 2020
- [j15]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: 185360-185372 (2020) - [j14]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: 188256-188268 (2020) - [j13]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: 195528-195540 (2020) - [j12]Theocharis Theocharides, Muhammad Shafique, Jungwook Choi, Onur Mutlu:
Guest Editorial: Robust Resource-Constrained Systems for Machine Learning. IEEE Des. Test 37(2): 5-7 (2020) - [j11]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): 30-57 (2020) - [j10]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): 36:1-36:19 (2020) - [j9]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): 2232-2250 (2020) - [c39]Junki Park, Hyunsung Yoon, Daehyun Ahn, Jungwook Choi, Jae-Joon Kim:
OPTIMUS: OPTImized matrix MUltiplication Structure for Transformer neural network accelerator. MLSys 2020 - [c38]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: 1-2 - [i8]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 abs/2002.04605 (2020) - [i7]Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung:
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks. CoRR abs/2009.14502 (2020)
2010 – 2019
- 2019
- [j8]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): 102-111 (2019) - [c37]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: 92-95 - [c36]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: 1-3 - [c35]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: 201 - [c34]Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan:
Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. HiPC 2019: 225-234 - [c33]Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung:
Workload-aware Automatic Parallelization for Multi-GPU DNN Training. ICASSP 2019: 1453-1457 - [c32]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 - [c31]Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang:
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators. IISWC 2019: 257-262 - [c30]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: 743-748 - [c29]Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Zhuo Wang, Pierce Chuang:
Accurate and Efficient 2-bit Quantized Neural Networks. SysML 2019 - [c28]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: 4901-4910 - [p1]Jungwook Choi, Swagath Venkataramani:
Approximate Computing Techniques for Deep Neural Networks. Approximate Circuits 2019: 307-329 - [i6]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 abs/1901.06588 (2019) - 2018
- [c27]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: 2827-2835 - [c26]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: 38:1-38:6 - [c25]Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani:
Exploiting approximate computing for deep learning acceleration. DATE 2018: 821-826 - [c24]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: 2346-2350 - [c23]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: 43-56 - [c22]Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang:
Taming the beast: Programming Peta-FLOP class Deep Learning Systems. ISLPED 2018: 18:1 - [c21]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: 35:1-35:2 - [c20]Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan:
Training Deep Neural Networks with 8-bit Floating Point Numbers. NeurIPS 2018: 7686-7695 - [c19]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: 35-36 - [i5]Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan:
PACT: Parameterized Clipping Activation for Quantized Neural Networks. CoRR abs/1805.06085 (2018) - [i4]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 abs/1807.06964 (2018) - [i3]Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung:
Workload-aware Automatic Parallelization for Multi-GPU DNN Training. CoRR abs/1811.01532 (2018) - [i2]Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan:
Training Deep Neural Networks with 8-bit Floating Point Numbers. CoRR abs/1812.08011 (2018) - 2017
- [c18]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: 146-147 - [c17]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: 57:1-57:2 - [c16]Tianqi Gao, Jungwook Choi, Shang-nien Tsai, Rob A. Rutenbar:
Toward a pixel-parallel architecture for graph cuts inference on FPGA. FPL 2017: 1-4 - [i1]Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan:
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. CoRR abs/1712.02679 (2017) - 2016
- [j7]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): 385-398 (2016) - [j6]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): 897-908 (2016) - [c15]Jungwook Choi, Rob A. Rutenbar:
Configurable and scalable belief propagation accelerator for computer vision. FPL 2016: 1-4 - [c14]Jungwook Choi, Ameya D. Patil, Rob A. Rutenbar, Naresh R. Shanbhag:
Analysis of error resiliency of belief propagation in computer vision. ICASSP 2016: 1060-1064 - [c13]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: 1-8 - [c12]Jinwook Oh, Jungwook Choi, Guilherme C. Januario, Kailash Gopalakrishnan:
Energy-Efficient Simultaneous Localization and Mapping via Compounded Approximate Computing. SiPS 2016: 51-56 - 2015
- [b1]Jungwook Choi:
High performance and error resilient probabilistic inference system for machine learning. University of Illinois Urbana-Champaign, USA, 2015 - [j5]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: 632590:1-632590:12 (2015) - [c11]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: 1-8 - 2014
- [c10]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: 8331-8335 - 2013
- [c9]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: 63-72 - [c8]Chuanjun Zhang, Glenn G. Ko, Jungwook Choi, Shang-nien Tsai, Minje Kim, Abner Guzmán-Rivera, Rob A. Rutenbar, Paris Smaragdis, Mi Sun Park, Vijaykrishnan Narayanan, Hongyi Xin, Onur Mutlu, Bin Li, Li Zhao, Mei Chen:
EMERALD: Characterization of emerging applications and algorithms for low-power devices. ISPASS 2013: 122-123 - [c7]Jungwook Choi, Rob A. Rutenbar:
FPGA acceleration of Markov Random Field TRW-S inference for stereo matching. MEMOCODE 2013: 139-142 - [c6]Jungwook Choi, Eric P. Kim, Rob A. Rutenbar, Naresh R. Shanbhag:
Error resilient MRF message passing architecture for stereo matching. SiPS 2013: 348-353 - 2012
- [j4]Jae-Ik Lee, Youngsup Song, Hakkyun Jung, Jungwook Choi, Youngkee Eun, Jongbaeg Kim:
Deformable Carbon Nanotube-Contact Pads for Inertial Microswitch to Extend Contact Time. IEEE Trans. Ind. Electron. 59(12): 4914-4920 (2012) - [j3]Kisun You, Jungwook Choi, Wonyong Sung:
Flexible and Expandable Speech Recognition Hardware with Weighted Finite State Transducers. J. Signal Process. Syst. 66(3): 235-244 (2012) - [c5]Jungwook Choi, Rob A. Rutenbar:
Hardware implementation of MRF map inference on an FPGA platform. FPL 2012: 209-216 - 2011
- [j2]Kisun You, Young-kyu Choi, Jungwook Choi, Wonyong Sung:
Memory Access Optimized VLSI for 5000-Word Continuous Speech Recognition. J. Signal Process. Syst. 63(1): 95-105 (2011) - 2010
- [j1]Young-kyu Choi, Kisun You, Jungwook Choi, Wonyong Sung:
A Real-Time FPGA-Based 20 000-Word Speech Recognizer With Optimized DRAM Access. IEEE Trans. Circuits Syst. I Regul. Pap. 57-I(8): 2119-2131 (2010) - [c4]Jungwook Choi, Kisun You, Wonyong Sung:
An FPGA implementation of speech recognition with weighted finite state transducers. ICASSP 2010: 1602-1605 - [c3]Jungwook Choi, Hyukjoon Lee:
Supporting handover in an IEEE 802.11p-based wireless access system. Vehicular Ad Hoc Networks 2010: 75-80
2000 – 2009
- 2009
- [c2]Young-kyu Choi, Kisun You, Jungwook Choi, Wonyong Sung:
VLSI for 5000-word continuous speech recognition. ICASSP 2009: 557-560 - 2006
- [c1]Seungwoo Kim, Dongik Oh, Dongwook Kim, Yongrae Jung, Jacil Choe, Jungwook Choi:
A Study on the Development of Ubiquitous CellPhone Robot. IROS 2006
Coauthor Index
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