Seung-Hwan Lim

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 45

Top Topics

Electron Microscopy

Top Venues

ICDM (Workshops)

Publications

Shruti R. Kulkarni, Anika Tabassum, Seung-Hwan Lim, Catherine D. Schuman, Bradley H. Theilman, Fred Rothganger, Felix Wang, James B. Aimone
Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning. NICE (2024)
Felix Wang, Shruti R. Kulkarni, Bradley H. Theilman, Fredrick H. Rothganger, Catherine D. Schuman, Seung-Hwan Lim, James B. Aimone
Scaling neural simulations in STACS. Neuromorph. Comput. Eng. 4 (2) (2024)
Seoyeon Bae, Yoon Kyung Lee, Jungcheol Lee, Jaeheon Kim, Haeseong Jeon, Seung-Hwan Lim, Byung-Cheol Kim, Sowon Hahn
Enhancing Empathy in Virtual Reality: An Embodied Approach to Mindset Modulation. CoRR (2024)
Michael J. Brim, Adam T. Moody, Seung-Hwan Lim, Ross G. Miller, Swen Boehm, Cameron Stanavige, Kathryn M. Mohror, Sarp Oral
UnifyFS: A User-level Shared File System for Unified Access to Distributed Local Storage. IPDPS (2023)
Ziyu Lu, Anika Tabassum, Shruti R. Kulkarni, Lu Mi, J. Nathan Kutz, Eric Shea-Brown, Seung-Hwan Lim
Attention for Causal Relationship Discovery from Biological Neural Dynamics. CoRR (2023)
Guojing Cong, Shruti R. Kulkarni, Seung-Hwan Lim, Prasanna Date, Shay Snyder, Maryam Parsa, Dominic Kennedy, Catherine D. Schuman
Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. ICMLA (2023)
Sandeep Polisetty, Juelin Liu, Kobi Falus, Yi Ren Fung, Seung-Hwan Lim, Hui Guan, Marco Serafini
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism. CoRR (2023)
Jiaji Ma, Seung-Hwan Lim
Efficient graph representation framework for chemical molecule similarity tasks. AIKE (2023)
Ramakrishnan Kannan, Piyush Sao, Hao Lu, Jakub Kurzak, Gundolf Schenk, Yongmei Shi, Seung-Hwan Lim, Sharat Israni, Vijay Thakkar, Guojing Cong, Robert M. Patton, Sergio E. Baranzini, Richard W. Vuduc, Thomas E. Potok
Exaflops Biomedical Knowledge Graph Analytics. SC (2022)
Evan Ezell, Seung-Hwan Lim, David Anderson, Robert Stewart
Community Fabric: Visualizing communities and structure in dynamic networks. Inf. Vis. 21 (2) (2022)
Guojing Cong, Seung-Hwan Lim, Steven Young
Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning. ICDM (Workshops) (2022)
Guojing Cong, Seung-Hwan Lim, Shruti R. Kulkarni, Prasanna Date, Thomas E. Potok, Shay Snyder, Maryam Parsa, Catherine D. Schuman
Semi-Supervised Graph Structure Learning on Neuromorphic Computers. ICONS (2022)
Robert M. Patton, Prasanna Date, Shruti R. Kulkarni, Chathika Gunaratne, Seung-Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman
Neuromorphic Computing for Scientific Applications. RSDHA@SC (2022)
Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC (2021)
Seung-Hwan Lim, Junghoon Chae, Guojing Cong, Drahomira Herrmannova, Robert M. Patton, Ramakrishnan Kannan, Thomas E. Potok
Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis. IEEE BigData (2021)
Guojing Cong, Seung-Hwan Lim
Versatile feature learning with graph convolutions and graph structures. ICDM (Workshops) (2021)
Edmon Begoli, Seung-Hwan Lim, Sudarshan Srinivasan
Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments. IEEE BigData (2021)
Shuai Yang, Xipeng Shen, Seung-Hwan Lim
Revisit the Scalability of Deep Auto-Regressive Models for Graph Generation. IJCNN (2021)
Hui Guan, Laxmikant Kishor Mokadam, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. MLSys (2020)
Sudip K. Seal, Seung-Hwan Lim, Dali Wang, Jacob D. Hinkle, Dalton D. Lunga, Aristeidis Tsaris
Toward Large-Scale Image Segmentation on Summit. ICPP (2020)
Moiz Arif, M. Mustafa Rafique, Seung-Hwan Lim, Zaki Malik
Infrastructure-Aware TensorFlow for Heterogeneous Datacenters. MASCOTS (2020)
Seung-Hwan Lim, Ross G. Miller, Sudharshan S. Vazhkudai
Understanding the Interplay between Hardware Errors and User Job Characteristics on the Titan Supercomputer. IPDPS (2020)
Hyogi Sim, Awais Khan, Sudharshan S. Vazhkudai, Seung-Hwan Lim, Ali Raza Butt, Youngjae Kim
An Integrated Indexing and Search Service for Distributed File Systems. IEEE Trans. Parallel Distributed Syst. 31 (10) (2020)
Jingoo Han, M. Mustafa Rafique, Luna Xu, Ali Raza Butt, Seung-Hwan Lim, Sudharshan S. Vazhkudai
MARBLE: A Multi-GPU Aware Job Scheduler for Deep Learning on HPC Systems. CCGRID (2020)
Robert M. Patton, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou
Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData (2019)
Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz
Exascale Deep Learning to Accelerate Cancer Research. CoRR (2019)
Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim
In-Place Zero-Space Memory Protection for CNN. CoRR (2019)
Jingoo Han, Luna Xu, M. Mustafa Rafique, Ali Raza Butt, Seung-Hwan Lim
A Quantitative Study of Deep Learning Training on Heterogeneous Supercomputers. CLUSTER (2019)
Hui Guan, Xipeng Shen, Seung-Hwan Lim
Wootz: a compiler-based framework for fast CNN pruning via composability. PLDI (2019)
Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim
In-Place Zero-Space Memory Protection for CNN. NeurIPS (2019)
Luna Xu, Ali Raza Butt, Seung-Hwan Lim, Ramakrishnan Kannan
A Heterogeneity-Aware Task Scheduler for Spark. CLUSTER (2018)
Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Don D. March, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Thomas P. Karnowski, Maxim A. Ziatdinov, Sergei V. Kalinin
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC (2018)
Alexander J. Paul, Dylan Lawrence, Myoungkyu Song, Seung-Hwan Lim, Chongle Pan, Tae-Hyuk Ahn
SORA: Scalable Overlap-graph Reduction Algorithms for Genome Assembly using Apache Spark in the Cloud. BIBM (2018)
Randall Pittman, Hui Guan, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton
Exploring flexible communications for streamlining DNN ensemble training pipelines. SC (2018)
Luna Xu, Seung-Hwan Lim, Min Li, Ali Raza Butt, Ramakrishnan Kannan
Scaling up data-parallel analytics platforms: Linear algebraic operation cases. IEEE BigData (2017)
Seung-Hwan Lim, Youngjae Kim
A quantitative model of application slow-down in multi-resource shared systems. Perform. Evaluation 108 (2017)
Hyogi Sim, Youngjae Kim, Sudharshan S. Vazhkudai, Geoffroy R. Vallée, Seung-Hwan Lim, Ali Raza Butt
Tagit: an integrated indexing and search service for file systems. SC (2017)
Seung-Hwan Lim, Hyogi Sim, Raghul Gunasekaran, Sudharshan S. Vazhkudai
Scientific user behavior and data-sharing trends in a petascale file system. SC (2017)
Seokyong Hong, Sangkeun Lee, Seung-Hwan Lim, Sreenivas R. Sukumar, Ranga Raju Vatsavai
Evaluation of Pattern Matching Workloads in Graph Analysis Systems. HPDC (2016)
Sudharshan S. Vazhkudai, John Harney, Raghul Gunasekaran, Dale Stansberry, Seung-Hwan Lim, Tom Barron, Andrew Nash, Arvind Ramanathan
Constellation: A science graph network for scalable data and knowledge discovery in extreme-scale scientific collaborations. IEEE BigData (2016)
John Harney, Seung-Hwan Lim, Sreenivas S. Sukumar, Dale Stansberry, Peter Xenopoulos
On-demand data analytics in HPC environments at leadership computing facilities: Challenges and experiences. IEEE BigData (2016)
Luna Xu, Seung-Hwan Lim, Ali Raza Butt, Sreenivas R. Sukumar, Ramakrishnan Kannan
FatMan vs. LittleBoy: Scaling Up Linear Algebraic Operations in Scale-Out Data Platforms. PDSW-DISCS@SC (2016)
Sangkeun Lee, Sreenivas R. Sukumar, Seokyong Hong, Seung-Hwan Lim
Enabling graph mining in RDF triplestores using SPARQL for holistic in-situ graph analysis. Expert Syst. Appl. 48 (2016)
Sreenivas R. Sukumar, Ramakrishnan Kannan, Seung-Hwan Lim, Michael A. Matheson
Kernels for scalable data analysis in science: Towards an architecture-portable future. IEEE BigData (2016)
Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim
Mini-apps for high performance data analysis. IEEE BigData (2016)
Sangkeun Lee, Sreenivas R. Sukumar, Seung-Hwan Lim
Graph mining meets the Semantic Web. ICDE Workshops (2015)
Sangkeun Lee, Byung H. Park, Seung-Hwan Lim, Mallikarjun Shankar
Table2Graph: A Scalable Graph Construction from Relational Tables Using Map-Reduce. BigDataService (2015)
Steven R. Young, Derek C. Rose, Thomas P. Karnowski, Seung-Hwan Lim, Robert M. Patton
Optimizing deep learning hyper-parameters through an evolutionary algorithm. MLHPC@SC (2015)
Seung-Hwan Lim, Sangkeun Lee, Gautam Ganesh, Tyler C. Brown, Sreenivas R. Sukumar
Graph Processing Platforms at Scale: Practices and Experiences. ISPASS (2015)
Seung-Hwan Lim, Gautam S. Thakur, James L. Horey
Analyzing Reliability of Virtual Machine Instances with Dynamic Pricing in the Public Cloud. IPDPS Workshops (2014)
Seung-Hwan Lim, James L. Horey, Yanjun Yao, Edmon Begoli, Qing Cao
Performance Implications from Sizing a VM on Multi-core Systems: A Data Analytic Application's View. IPDPS Workshops (2013)
Kyu-Hwang Kang, Seung-Hwan Lim, Sang-Wook Kim, Min-Hee Jang, Byeong-Soo Jeong
A Topic-Oriented Analysis of Information Diffusion in a Blogosphere. DEXA (2) (2012)
Bikash Sharma, Ramya Prabhakar, Seung-Hwan Lim, Mahmut T. Kandemir, Chita R. Das
MROrchestrator: A Fine-Grained Resource Orchestration Framework for MapReduce Clusters. IEEE CLOUD (2012)
Seung-Hwan Lim, Jae-Seok Huh, Youngjae Kim, Galen M. Shipman, Chita R. Das
D-factor: a quantitative model of application slow-down in multi-resource shared systems. SIGMETRICS (2012)
James L. Horey, Edmon Begoli, Raghul Gunasekaran, Seung-Hwan Lim, James J. Nutaro
Big Data Platforms as a Service: Challenges and Approach. HotCloud (2012)
Seung-Hwan Lim, Bikash Sharma, Byung-Chul Tak, Chita R. Das
A dynamic energy management scheme for multi-tier data centers. ISPASS (2011)
Seung-Hwan Lim, Sang-Wook Kim, Soyoun Kim, Sanghyun Park
Construction of a blog network based on information diffusion. SAC (2011)
Seung-Hwan Lim, Jae-Seok Huh, Youngjae Kim, Chita R. Das
Migration, Assignment, and Scheduling of Jobs in Virtualized Environment. HotCloud (2011)
Seung-Hwan Lim, Sang-Wook Kim, Sunju Park, Joon Ho Lee
Determining Content Power Users in a Blog Network: An Approach and Its Applications. IEEE Trans. Syst. Man Cybern. Part A 41 (5) (2011)
Yong-Suk Kwon, Sang-Wook Kim, Sunju Park, Seung-Hwan Lim, Jae Bum Lee
The information diffusion model in the blog world. SNAKDD (2009)
Seung-Hwan Lim, Sang-Wook Kim, Sunju Park, Joon Ho Lee
Determining content power users in a blog network. SNAKDD (2009)
Gunwoo Nam, Pushkar Patankar, Seung-Hwan Lim, Bikash Sharma, George Kesidis, Chita R. Das
Clock-like Flow Replacement Schemes for Resilient Flow Monitoring. ICDCS (2009)
Seung-Hwan Lim, Bikash Sharma, Gunwoo Nam, Eun-Kyoung Kim, Chita R. Das
MDCSim: A multi-tier data center simulation, platform. CLUSTER (2009)
Seung-Hwan Lim, Heejin Park, Sang-Wook Kim
Using multiple indexes for efficient subsequence matching in time-series databases. Inf. Sci. 177 (24) (2007)
Seung-Hwan Lim, Heejin Park, Sang-Wook Kim
Using Multiple Indexes for Efficient Subsequence Matching in Time-Series Databases. DASFAA (2006)