A^3: Accelerating Neural Network Attention Mechanism with Approximation (Tae Jun Ham, Seonghak Kim, and Sung Jun Jung, Young H. Oh, Yeonhong Park, Yoon Ho Song, Junghoon Park, Sanghee Lee, Kyoung Park, Jae W. Lee, and Deog-Kyoon Jeong) #이재욱 교수팀

 FVM: FPGA-assisted Virtual Device Emulation for Fast, Scalable, and Flexible Virtualization (Dongup Kwon, Junehyuk Boo, Dongryeong Kim, and Jangwoo Kim) #김장우 교수팀 

TrainBox: An Extreme-Scale Neural Network Training Server by Systematically Balancing Operations (Pyeongsu Park, Heetak Jeong, and Jangwoo Kim) #김장우 교수팀

SuperNPU: An Extremely Fast Neural Processing Unit Using Superconducting Logic Devices (Koki Ishida, Il-Kwon Byun, Ikki Nagoka, Kosuke Fukumitsu, Masamitsu Tanaka, Satoshi Kwakami, Teruo Tanimoto, Takatsugu Ono, Jangwoo Kim, and Koji Inoue) #김장우 교수팀

Graphene: Strong yet Lightweight Row Hammer Protection (Yeonhong Park, Woosuk Kwon, Eojin Lee, Tae Jun Ham, Jung Ho Ahn, and Jae W. Lee) #이재욱 교수팀 

CryoCore: A Fast and Dense Processor Architecture for Cryogenic Computing (Ilkwon Byun, Dongmoon Min, Gyu-Hyeon Lee, Seongmin Na, and Jangwoo Kim) #김장우 교수팀

A Multi-Neural Network Acceleration Architecture (Eunjin Baek, Dongup Kwon, and Jangwoo Kim) #김장우 교수팀

Genesis: A Hardware Acceleration Framework for Genomic Data Analysis (Tae Jun Ham, David Bruns-Smith, Brendan Sweeney, Yejin Lee, Seong Hoon Seo, U Gyeong Song, Young H. Oh, Krste Asanovic, Jae W. Lee, and Lisa Wu Wills) #이재욱 교수팀

A Specialized Architecture for Object Serialization with Applications to Big Data Analytics (Jaeyoung Jang, Sung Jun Jung, Sunmin Jeong, Jun Heo, Hoon Shin, Tae Jun Ham, and Jae W. Lee) #이재욱 교수팀

A Case for Hardware-Based Demand Paging (Gyusun Lee, Wenjing Jin, Wonsuk Song, Jeonghun Gong, Jonghyun Bae, Tae Jun Ham, Jae W. Lee, and Jinkyu Jeong) #이재욱 교수팀 

Enforcing Last-Level Cache Partitioning through Memory Virtual Channels (Jongwook Chung, Yuhwan Ro, Joonsung Kim, Jaehyung Ahn, Jangwoo Kim, John Kim, Jae W.Lee, Jung Ho Ahn) #안정호 교수팀

A 65nm 236.5nJ/Classification Neuromorphic Processor with 7.5% Energy Overhead On-Chip Learning Using Direct Spike-Only Feedback (Jeongwoo Park, Juyun Lee, Dongsuk Jeon) #전동석 교수팀

FA3C: FPGA-Accelerated Deep Reinforcement Learning (Hyungmin Cho, Pyeongseok Oh, Jiyoung Park, Wookeun Jung, Jaejin Lee) #이재진 교수팀

Apache Nemo: A Framework for Building Distributed Dataflow Optimization Policies (Youngseok Yang, Jeongyoon Eo, Geon-Woo Kim, Joo Yeon Kim, Sanha Lee, Jangho Seo, Won Wook Song, Byung-Gon Chun) #전병곤 교수팀

μLayer: Low Latency On-Device Inference Using Cooperative Single-Layer Acceleration and Processor-Friendly Quantization (Youngsok Kim, Joonsung Kim, Dongju Chae, Daehyun Kim, and Jangwoo Kim) #김장우 교수팀

Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks (Soojeong Kim, Gyeong-In Yu, Hojin Park, Sungwoo Cho, Eunji Jeong, Hyeonmin Ha, Sanha Lee, Joo Seong Jeong, Byung-Gon Chun) #전병곤 교수팀

MnnFast: A Fast and Scalable System Architecture for Memory-Augmented Neural Networks (Hanhwi Jang, Joonsung Kim, Jae-Eon Jo, Jaewon Lee, and Jangwoo Kim) #김장우 교수팀

Cryogenic Computer Architecture Modeling with Memory-Side Case Studies (Gyuhyeon Lee, Dongmoon Min, Ilkwon Byun, and Jangwoo Kim) #김장우 교수팀

TWiCe: Preventing Row-hammering by Exploiting Time Window Counters (Eojin Lee, Ingab Kang, Sukhan Lee, G. Edward Suh, Jung Ho Ahn) #안정호 교수팀

JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs (Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Byung-Gon Chun) #전병곤 교수팀

Restructuring Batch Normalization to Accelerate CNN Training (Wonkyung Jung , Daejin Jung , Byeongho Kim, Sunjung Lee, Wonjong Rhee, Jung Ho Ahn) #안정호 교수팀

Demonstration of JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs (Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dong-Jin Shin, Byung-Gon Chun) – Demo #전병곤 교수팀

Speculative Symbolic Graph Execution of Imperative Deep Learning Programs (Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jung, Dong-Jin Shin, Taebum Kim, Byung-Gon Chun) #전병곤 교수팀

PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems (Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Markus Weimer, Matteo Interlandi) #전병곤 교수팀

A Portable, Automatic Data Quantizer for Deep Neural Networks (Young H. Oh, Quan Quan, Daeyeon Kim, Seonghak Kim, Jun Heo, Sungjun Jung, Jaeyoung Jang, Jae W. Lee) #이재욱 교수팀

3D-Xpath: high-density managed DRAM architecture with cost-effective alternative paths for memory transactions (Sukhan Lee, Kiwon Lee, Minchul Sung, Mohammad Alian, Chankyung Kim, Wooyeong Cho, Reum Oh, Seongil O, Jung Ho Ahn, and Nam Sung Kim) #안정호 교수팀