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Joo-Young Kim 0001
Person information
- affiliation: Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
- affiliation (since 2010): Microsoft Research, Redmond, WA, USA
Other persons with the same name
- Joo-Young Kim 0002 — K-JIST, Gwangju, South Korea
- Joo-Young Kim 0003 — Tongmyung University, Distribution Management Department, Busan, South Korea
- Joo-Young Kim 0004 — Yonsei University, Seoul, South Korea
- Joo Young Kim 0005
(aka: Joo-Young Kim 0005) — Hanyang University, Department of Biomedical Engineering, Seoul, South Korea
- Joo-Young Kim 0006 — HyperAccel, Hwaseong-si, South Korea
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2020 – today
- 2024
- [j33]Ji-Hoon Kim
, Seunghee Han
, Kwanghyun Park
, Soo-Young Ji, Joo-Young Kim
:
Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics. IEEE Access 12: 11945-11962 (2024) - [j32]Junsoo Kim
, Seunghee Han
, Geonwoo Ko
, Ji-Hoon Kim
, Changha Lee
, Taewoo Kim
, Chan-Hyun Youn
, Joo-Young Kim
:
EPU: An Energy-Efficient Explainable AI Accelerator With Sparsity-Free Computation and Heat Map Compression/Pruning. IEEE J. Solid State Circuits 59(3): 830-841 (2024) - [j31]Jaehoon Heo
, Jung-Hoon Kim
, Wontak Han
, Jaeuk Kim
, Joo-Young Kim
:
SP-PIM: A Super-Pipelined Processing-In-Memory Accelerator With Local Error Prediction for Area/Energy-Efficient On-Device Learning. IEEE J. Solid State Circuits 59(8): 2671-2683 (2024) - [c45]Jinho Yang, Sungwoong Yune, Sukbin Lim, Donghyuk Kim, Joo-Young Kim:
ACane: An Efficient FPGA-based Embedded Vision Platform with Accumulation-as-Convolution Packing for Autonomous Mobile Robots. ASPDAC 2024: 533-538 - [c44]Sukbin Lim
, Jaehoon Heo, Jinho Yang, Joo-Young Kim:
A 38.5TOPS/W Point Cloud Neural Network Processor with Virtual Pillar and Quadtree-based Workload Management for Real-Time Outdoor BEV Detection. CICC 2024: 1-2 - [c43]Prasetiyo
, Adiwena Putra, Joo-Young Kim:
Morphling: A Throughput-Maximized TFHE-based Accelerator using Transform-domain Reuse. HPCA 2024: 249-262 - [c42]Seunghee Han, Seungjae Moon, Teokkyu Suh, Jaehoon Heo, Joo-Young Kim:
BLESS: Bandwidth and Locality Enhanced SMEM Seeding Acceleration for DNA Sequencing. ISCA 2024: 582-596 - [i9]Wontak Han, Hyunjun Cho, Donghyuk Kim, Joo-Young Kim:
SAL-PIM: A Subarray-level Processing-in-Memory Architecture with LUT-based Linear Interpolation for Transformer-based Text Generation. CoRR abs/2401.17005 (2024) - 2023
- [j30]Ji-Hoon Kim, Sungyeob Yoo, Joo-Young Kim:
South Korea's Nationwide Effort for AI Semiconductor Industry. Commun. ACM 66(7): 46-51 (2023) - [j29]Jaehoon Heo
, Junsoo Kim
, Sukbin Lim
, Wontak Han
, Joo-Young Kim
:
T-PIM: An Energy-Efficient Processing-in-Memory Accelerator for End-to-End On-Device Training. IEEE J. Solid State Circuits 58(3): 600-613 (2023) - [j28]SeongHwan Cho
, Joo-Young Kim
, Minoru Fujishima
, Jun Zhou
:
Introduction to the Special Section on the 2022 Asian Solid-State Circuits Conference (A-SSCC). IEEE J. Solid State Circuits 58(10): 2671-2674 (2023) - [j27]Ji-Hoon Kim
, Yeo-Reum Park, Jaeyoung Do
, Soo-Young Ji, Joo-Young Kim:
Accelerating Large-Scale Graph-Based Nearest Neighbor Search on a Computational Storage Platform. IEEE Trans. Computers 72(1): 278-290 (2023) - [j26]Prasetiyo
, Seongmin Hong, Yashael Faith Arthanto, Joo-Young Kim
:
Accelerating Deep Convolutional Neural Networks Using Number Theoretic Transform. IEEE Trans. Circuits Syst. I Regul. Pap. 70(1): 315-326 (2023) - [j25]Donghyuk Kim
, Sanghyun Jeong
, Joo-Young Kim
:
Agamotto: A Performance Optimization Framework for CNN Accelerator With Row Stationary Dataflow. IEEE Trans. Circuits Syst. I Regul. Pap. 70(6): 2487-2496 (2023) - [c41]Junsoo Kim, Geonwoo Ko, Ji-Hoon Kim, Changha Lee, Taewoo Kim, Chan-Hyun Youn, Joo-Young Kim:
A 26.55TOPS/W Explainable AI Processor with Dynamic Workload Allocation and Heat Map Compression/Pruning. CICC 2023: 1-2 - [c40]Je Yang, Sukbin Lim
, Sukjin Lee, Jae-Young Kim, Joo-Young Kim:
JNPU: A 1.04TFLOPS Joint-DNN Training Processor with Speculative Cyclic Quantization and Triple Heterogeneity on Microarchitecture / Precision / Dataflow. ESSCIRC 2023: 349-352 - [c39]Sungyeob Yoo, Hyunsung Kim, Jinseok Kim, Sunghyun Park, Joo-Young Kim, Jinwook Oh:
LightTrader: A Standalone High-Frequency Trading System with Deep Learning Inference Accelerators and Proactive Scheduler. HPCA 2023: 1017-1030 - [c38]Jaehoon Heo, Yongwon Shin
, Sangjin Choi, Sungwoong Yune, Jung-Hoon Kim, Hyojin Sung, Youngjin Kwon, Joo-Young Kim:
PRIMO: A Full-Stack Processing-in-DRAM Emulation Framework for Machine Learning Workloads. ICCAD 2023: 1-9 - [c37]Adiwena Putra
, Prasetiyo
, Yi Chen
, John Kim
, Joo-Young Kim
:
Strix: An End-to-End Streaming Architecture with Two-Level Ciphertext Batching for Fully Homomorphic Encryption with Programmable Bootstrapping. MICRO 2023: 1319-1331 - [c36]Jung-Hoon Kim, Jaehoon Heo, Wontak Han, Jaeuk Kim, Joo-Young Kim:
SP-PIM: A 22.41TFLOPS/W, 8.81Epochs/Sec Super-Pipelined Processing-In-Memory Accelerator with Local Error Prediction for On-Device Learning. VLSI Technology and Circuits 2023: 1-2 - [i8]Adiwena Putra, Prasetiyo, Yi Chen, John Kim, Joo-Young Kim:
Strix: An End-to-End Streaming Architecture with Two-Level Ciphertext Batching for Fully Homomorphic Encryption with Programmable Bootstrapping. CoRR abs/2305.11423 (2023) - [i7]Donghyuk Kim, Jae-Young Kim, Wontak Han, Jongsoon Won, Haerang Choi, Yongkee Kwon, Joo-Young Kim:
Darwin: A DRAM-based Multi-level Processing-in-Memory Architecture for Data Analytics. CoRR abs/2305.13970 (2023) - 2022
- [j24]Taewoo Kim
, Minsu Jeon
, Changha Lee
, Junsoo Kim
, Geonwoo Ko, Joo-Young Kim
, Chan-Hyun Youn
:
Federated Onboard-Ground Station Computing With Weakly Supervised Cascading Pyramid Attention Network for Satellite Image Analysis. IEEE Access 10: 117315-117333 (2022) - [j23]Gyeongcheol Shin
, Junsoo Kim
, Joo-Young Kim
:
OpenMDS: An Open-Source Shell Generation Framework for High-Performance Design on Xilinx Multi-Die FPGAs. IEEE Comput. Archit. Lett. 21(2): 101-104 (2022) - [j22]Tony Tae-Hyoung Kim
, Bongjin Kim, Joo-Young Kim
, Jaydeep P. Kulkarni
:
Guest Editorial Revolution of AI and Machine Learning With Processing-in-Memory (PIM): From Systems, Architectures, to Circuits. IEEE J. Emerg. Sel. Topics Circuits Syst. 12(2): 333-337 (2022) - [j21]Donghyuk Kim
, Chengshuo Yu
, Shanshan Xie, Yuzong Chen
, Joo-Young Kim
, Bongjin Kim
, Jaydeep P. Kulkarni
, Tony Tae-Hyoung Kim
:
An Overview of Processing-in-Memory Circuits for Artificial Intelligence and Machine Learning. IEEE J. Emerg. Sel. Topics Circuits Syst. 12(2): 338-353 (2022) - [j20]Wontak Han
, Jaehoon Heo
, Junsoo Kim
, Sukbin Lim
, Joo-Young Kim
:
Design of Processing-in-Memory With Triple Computational Path and Sparsity Handling for Energy-Efficient DNN Training. IEEE J. Emerg. Sel. Topics Circuits Syst. 12(2): 354-366 (2022) - [c35]Jaehoon Heo, Junsoo Kim, Wontak Han, Sukbin Lim
, Joo-Young Kim:
T-PIM: A 2.21-to-161.08TOPS/W Processing-In-Memory Accelerator for End-to-End On-Device Training. CICC 2022: 1-2 - [c34]Yeo-Reum Park, Ji-Hoon Kim, Jaeyoung Do, Joo-Young Kim:
A Dual-Mode Similarity Search Accelerator based on Embedding Compression for Online Cross-Modal Image-Text Retrieval. FCCM 2022: 1-9 - [c33]Gyeongcheol Shin, Junsoo Kim, Joo-Young Kim:
OpenMDS: An Open-Source Shell Generation Framework for High-Performance Design on Multi-Die FPGAs. FCCM 2022: 1 - [c32]Yashael Faith Arthanto, David Ojika, Joo-Young Kim:
FSHMEM: Supporting Partitioned Global Address Space on FPGAs for Large-Scale Hardware Acceleration Infrastructure. FPL 2022: 218-224 - [c31]Je Yang
, Jaeuk Kim, Joo-Young Kim:
LearningGroup: A Real-Time Sparse Training on FPGA via Learnable Weight Grouping for Multi-Agent Reinforcement Learning. FPT 2022: 1-9 - [c30]Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim
, Dongsoo Lee, Joo-Young Kim:
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. HCS 2022: 1-17 - [c29]Ji-Hoon Kim, Seunghee Han, Kwanghyun Park
, Soo-Young Ji, Joo-Young Kim:
Trinity: End-to-End In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics. HCS 2022: 1-16 - [c28]Hyunsung Kim, Sungyeob Yoo, Jaewan Bae, Kyeongryeol Bong, Yoonho Boo, Karim Charfi, Hyo-Eun Kim, Hyun Suk Kim, Jinseok Kim, Byungjae Lee, Jaehwan Lee, Myeongbo Shim, Sungho Shin, Jeong Seok Woo, Joo-Young Kim, Sunghyun Park, Jinwook Oh:
LightTrader : World's first AI-enabled High-Frequency Trading Solution with 16 TFLOPS / 64 TOPS Deep Learning Inference Accelerators. HCS 2022: 1-10 - [c27]Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim
, Dongsoo Lee, Joo-Young Kim:
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. MICRO 2022: 616-630 - [i6]Jung-Hoon Kim, Sungyeob Yoo, Seungjae Moon, Joo-Young Kim:
Exploration of Systolic-Vector Architecture with Resource Scheduling for Dynamic ML Workloads. CoRR abs/2206.03060 (2022) - [i5]Yashael Faith Arthanto, David Ojika, Joo-Young Kim:
FSHMEM: Supporting Partitioned Global Address Space on FPGAs for Large-Scale Hardware Acceleration Infrastructure. CoRR abs/2207.04625 (2022) - [i4]Ji-Hoon Kim, Yeo-Reum Park, Jaeyoung Do, Soo Young Ji, Joo-Young Kim:
Accelerating Large-Scale Graph-based Nearest Neighbor Search on a Computational Storage Platform. CoRR abs/2207.05241 (2022) - [i3]Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim, Dongsoo Lee, Joo-Young Kim:
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. CoRR abs/2209.10797 (2022) - [i2]Je Yang, Jaeuk Kim, Joo-Young Kim:
LearningGroup: A Real-Time Sparse Training on FPGA via Learnable Weight Grouping for Multi-Agent Reinforcement Learning. CoRR abs/2210.16624 (2022) - 2021
- [j19]Joo-Young Kim:
Chapter Five - FPGA based neural network accelerators. Adv. Comput. 122: 135-165 (2021) - [j18]Ji-Hoon Kim
, Juhyoung Lee
, Jinsu Lee
, Jaehoon Heo
, Joo-Young Kim:
Z-PIM: A Sparsity-Aware Processing-in-Memory Architecture With Fully Variable Weight Bit-Precision for Energy-Efficient Deep Neural Networks. IEEE J. Solid State Circuits 56(4): 1093-1104 (2021) - [c26]Je Yang
, Seongmin Hong, Joo-Young Kim:
FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism. DAC 2021: 259-264 - [c25]Ji-Hoon Kim, Yeo-Reum Park, Jaeyoung Do, Soo Young Ji, Joo-Young Kim:
Accelerating Large-Scale Nearest Neighbor Search with Computational Storage Device. FCCM 2021: 254 - [i1]Je Yang, Seongmin Hong, Joo-Young Kim:
FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism. CoRR abs/2102.12103 (2021) - 2020
- [c24]Ji-Hoon Kim, Juhyoung Lee, Jinsu Lee, Hoi-Jun Yoo, Joo-Young Kim:
Z-PIM: An Energy-Efficient Sparsity Aware Processing-In-Memory Architecture with Fully-Variable Weight Precision. VLSI Circuits 2020: 1-2
2010 – 2019
- 2017
- [j17]Adrian M. Caulfield, Eric S. Chung, Andrew Putnam
, Hari Angepat, Daniel Firestone, Jeremy Fowers, Michael Haselman, Stephen Heil, Matt Humphrey, Puneet Kaur, Joo-Young Kim, Daniel Lo, Todd Massengill, Kalin Ovtcharov, Michael Papamichael, Lisa Woods, Sitaram Lanka, Derek Chiou, Doug Burger:
Configurable Clouds. IEEE Micro 37(3): 52-61 (2017) - 2016
- [j16]Andrew Putnam
, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinides, John Demme, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James R. Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger:
A reconfigurable fabric for accelerating large-scale datacenter services. Commun. ACM 59(11): 114-122 (2016) - [c23]Adrian M. Caulfield, Eric S. Chung, Andrew Putnam
, Hari Angepat, Jeremy Fowers, Michael Haselman, Stephen Heil, Matt Humphrey, Puneet Kaur, Joo-Young Kim, Daniel Lo, Todd Massengill, Kalin Ovtcharov, Michael Papamichael, Lisa Woods, Sitaram Lanka, Derek Chiou, Doug Burger:
A cloud-scale acceleration architecture. MICRO 2016: 7:1-7:13 - 2015
- [j15]Andrew Putnam
, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinides, John Demme, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James R. Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger:
A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services. IEEE Micro 35(3): 10-22 (2015) - [c22]Jeremy Fowers, Joo-Young Kim, Doug Burger, Scott Hauck:
A Scalable High-Bandwidth Architecture for Lossless Compression on FPGAs. FCCM 2015: 52-59 - [c21]Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, Eric S. Chung:
Toward accelerating deep learning at scale using specialized hardware in the datacenter. Hot Chips Symposium 2015: 1-38 - 2014
- [c20]Janarbek Matai, Joo-Young Kim, Ryan Kastner
:
Energy efficient canonical huffman encoding. ASAP 2014: 202-209 - [c19]Joo-Young Kim, Scott Hauck, Doug Burger:
A Scalable Multi-engine Xpress9 Compressor with Asynchronous Data Transfer. FCCM 2014: 161-164 - [c18]Andrew Putnam
, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinides, John Demme, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James R. Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger:
A reconfigurable fabric for accelerating large-scale datacenter services. ISCA 2014: 13-24 - 2013
- [j14]Jinwook Oh, Gyeonghoon Kim, Junyoung Park, Injoon Hong, Seungjin Lee, Joo-Young Kim, Jeong-Ho Woo, Hoi-Jun Yoo:
A 320 mW 342 GOPS Real-Time Dynamic Object Recognition Processor for HD 720p Video Streams. IEEE J. Solid State Circuits 48(1): 33-45 (2013) - 2012
- [j13]Junyoung Park, Joonsoo Kwon, Jinwook Oh, Seungjin Lee, Joo-Young Kim, Hoi-Jun Yoo:
A 92-mW Real-Time Traffic Sign Recognition System With Robust Illumination Adaptation and Support Vector Machine. IEEE J. Solid State Circuits 47(11): 2711-2723 (2012) - [j12]Jinwook Oh, Gyeonghoon Kim, Injoon Hong, Junyoung Park, Seungjin Lee, Joo-Young Kim, Jeong-Ho Woo, Hoi-Jun Yoo:
Low-Power, Real-Time Object-Recognition Processors for Mobile Vision Systems. IEEE Micro 32(6): 38-50 (2012) - [c17]Jinwook Oh, Gyeonghoon Kim, Junyoung Park, Injoon Hong, Seungjin Lee, Joo-Young Kim, Hoi-Jun Yoo:
A simultaneous multithreading heterogeneous object recognition processor with machine learning based dynamic resource management. COOL Chips 2012: 1-3 - 2011
- [j11]Seungjin Lee, Minsu Kim, Kwanho Kim, Joo-Young Kim, Hoi-Jun Yoo:
24-GOPS 4.5-mm2 Digital Cellular Neural Network for Rapid Visual Attention in an Object-Recognition SoC. IEEE Trans. Neural Networks 22(1): 64-73 (2011) - 2010
- [j10]Joo-Young Kim, Minsu Kim, Seungjin Lee, Jinwook Oh, Kwanho Kim, Hoi-Jun Yoo:
A 201.4 GOPS 496 mW Real-Time Multi-Object Recognition Processor With Bio-Inspired Neural Perception Engine. IEEE J. Solid State Circuits 45(1): 32-45 (2010) - [j9]Joo-Young Kim, Junyoung Park, Seungjin Lee, Minsu Kim, Jinwook Oh, Hoi-Jun Yoo:
A 118.4 GB/s Multi-Casting Network-on-Chip With Hierarchical Star-Ring Combined Topology for Real-Time Object Recognition. IEEE J. Solid State Circuits 45(7): 1399-1409 (2010) - [j8]Seungjin Lee, Kwanho Kim, Joo-Young Kim, Minsu Kim, Hoi-Jun Yoo:
Familiarity based unified visual attention model for fast and robust object recognition. Pattern Recognit. 43(3): 1116-1128 (2010) - [j7]Joo-Young Kim, Sejong Oh, Seungjin Lee, Minsu Kim, Jinwook Oh, Hoi-Jun Yoo:
An attention controlled multi-core architecture for energy efficient object recognition. Signal Process. Image Commun. 25(5): 363-376 (2010) - [j6]Joo-Young Kim, Donghyun Kim, Seungjin Lee, Kwanho Kim, Hoi-Jun Yoo:
Visual Image Processing RAM: Memory Architecture With 2-D Data Location Search and Data Consistency Management for a Multicore Object Recognition Processor. IEEE Trans. Circuits Syst. Video Technol. 20(4): 485-495 (2010) - [c16]Seungjin Lee, Jinwook Oh, Minsu Kim, Junyoung Park, Joonsoo Kwon, Joo-Young Kim, Hoi-Jun Yoo:
Intelligent NoC with neuro-fuzzy bandwidth regulation for a 51 IP object recognition processor. CICC 2010: 1-4
2000 – 2009
- 2009
- [j5]Donghyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Hoi-Jun Yoo:
Memory-centric network-on-chip for power efficient execution of task-level pipeline on a multi-core processor. IET Comput. Digit. Tech. 3(5): 513-524 (2009) - [j4]Kwanho Kim, Seungjin Lee, Joo-Young Kim, Minsu Kim, Hoi-Jun Yoo:
A 125 GOPS 583 mW Network-on-Chip Based Parallel Processor With Bio-Inspired Visual Attention Engine. IEEE J. Solid State Circuits 44(1): 136-147 (2009) - [j3]Joo-Young Kim, Minsu Kim, Seungjin Lee, Jinwook Oh, Sejong Oh, Hoi-Jun Yoo:
Real-Time Object Recognition with Neuro-Fuzzy Controlled Workload-Aware Task Pipelining. IEEE Micro 29(6): 28-43 (2009) - [j2]Kwanho Kim, Seungjin Lee, Joo-Young Kim, Minsu Kim, Hoi-Jun Yoo:
A Configurable Heterogeneous Multicore Architecture With Cellular Neural Network for Real-Time Object Recognition. IEEE Trans. Circuits Syst. Video Technol. 19(11): 1612-1622 (2009) - [j1]Donghyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Se-Joong Lee, Hoi-Jun Yoo:
81.6 GOPS Object Recognition Processor Based on a Memory-Centric NoC. IEEE Trans. Very Large Scale Integr. Syst. 17(3): 370-383 (2009) - [c15]Minsu Kim, Joo-Young Kim, Seungjin Lee, Jinwook Oh, Hoi-Jun Yoo:
A 54GOPS 51.8mW analog-digital mixed mode Neural Perception Engine for fast object detection. CICC 2009: 649-652 - [c14]Joo-Young Kim, Kwanho Kim, Seungjin Lee, Minsu Kim, Jinwook Oh, Hoi-Jun Yoo:
A 118.4GB/s multi-casting network-on-chip for real-time object recognition processor. ESSCIRC 2009: 400-403 - [c13]Joo-Young Kim, Seungjin Lee, Jinwook Oh, Minsu Kim, Hoi-Jun Yoo:
A 60fps 496mW multi-object recognition processor with workload-aware dynamic power management. ISLPED 2009: 365-370 - [c12]Joo-Young Kim, Minsu Kim, Seungjin Lee, Jinwook Oh, Kwanho Kim, Sejong Oh, Jeong-Ho Woo, Donghyun Kim, Hoi-Jun Yoo:
A 201.4GOPS 496mW real-time multi-object recognition processor with bio-inspired neural perception engine. ISSCC 2009: 150-151 - 2008
- [c11]Donghyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Hoi-Jun Yoo:
Vision platform for mobile intelligent robot based on 81.6 GOPS object recognition processor. DAC 2008: 96-101 - [c10]Kwanho Kim, Joo-Young Kim, Seungjin Lee, Minsu Kim, Hoi-Jun Yoo:
A 211 GOPS/W dual-mode real-time object recognition processor with Network-on-Chip. ESSCIRC 2008: 462-465 - [c9]Joonsung Bae, Joo-Young Kim, Hoi-Jun Yoo:
A 0.6pJ/b 3Gb/s/ch transceiver in 0.18 µm CMOS for 10mm on-chip interconnects. ISCAS 2008: 2861-2864 - [c8]Kwanho Kim, Seungjin Lee, Joo-Young Kim, Minsu Kim, Donghyun Kim, Jeong-Ho Woo, Hoi-Jun Yoo:
A 125GOPS 583mW Network-on-Chip Based Parallel Processor with Bio-inspired Visual-Attention Engine. ISSCC 2008: 308-309 - 2007
- [c7]Donghyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Hoi-Jun Yoo:
An 81.6 GOPS Object Recognition Processor Based on NoC and Visual Image Processing Memory. CICC 2007: 443-446 - [c6]Joo-Young Kim, Donghyun Kim, Seungjin Lee, Kwanho Kim, Seonghyun Jeon, Hoi-Jun Yoo:
Visual image processing RAM for fast 2-D data location search. ESSCIRC 2007: 324-327 - [c5]Donghyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Hoi-Jun Yoo:
Solutions for Real Chip Implementation Issues of NoC and Their Application to Memory-Centric NoC. NOCS 2007: 30-39 - 2006
- [c4]Sungdae Choi, Seong-Jun Song, Kyomin Sohn, Hyejung Kim, Joo-Young Kim, Namjun Cho, Jeong-Ho Woo, Jerald Yoo
, Hoi-Jun Yoo:
A Multi-Nodes Human Body Communication Sensor Network Control Processor. CICC 2006: 109-112 - [c3]Joo-Young Kim, Kangmin Lee, Hoi-Jun Yoo:
A 372 ps 64-bit adder using fast pull-up logic in 0.18µm CMOS. ISCAS 2006 - [c2]Sungdae Choi, Kyomin Sohn, Hyejung Kim, Joo-Young Kim, Seong-Jun Song, Namjun Cho, Jerald Yoo
, Hoi-Jun Yoo:
An Ultra Low-Power Body Sensor Network Control Processor with Centralized Node Control. SoC 2006: 1-4 - [c1]Sungdae Choi, Seong-Jun Song, Kyomin Sohn, Hyejung Kim, Joo-Young Kim, Jerald Yoo
, Hoi-Jun Yoo:
A Low-power Star-topology Body Area Network Controller for Periodic Data Monitoring Around and Inside the Human Body. ISWC 2006: 139-140
Coauthor Index
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