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Seung-Hwan Lim
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2020 – today
- 2024
- [j7]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): 24002 (2024) - [c53]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: 1-7 - [i5]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 abs/2404.00300 (2024) - 2023
- [c52]Jiaji Ma, Seung-Hwan Lim:
Efficient graph representation framework for chemical molecule similarity tasks. AIKE 2023: 113-120 - [c51]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: 1541-1546 - [c50]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: 290-300 - [i4]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 abs/2303.13775 (2023) - [i3]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 abs/2311.06928 (2023) - 2022
- [j6]Evan Ezell
, Seung-Hwan Lim, David Anderson, Robert N. Stewart
:
Community Fabric: Visualizing communities and structure in dynamic networks. Inf. Vis. 21(2): 130-142 (2022) - [c49]Guojing Cong, Seung-Hwan Lim, Steven Young:
Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning. ICDM (Workshops) 2022: 23-30 - [c48]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: 28:1-28:4 - [c47]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: 6:1-6:11 - [c46]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: 22-28 - 2021
- [c45]Edmon Begoli, Seung-Hwan Lim, Sudarshan Srinivasan:
Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments. IEEE BigData 2021: 3095-3100 - [c44]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: 4381-4386 - [c43]Shuai Yang, Xipeng Shen
, Seung-Hwan Lim:
Revisit the Scalability of Deep Auto-Regressive Models for Graph Generation. IJCNN 2021: 1-8 - [c42]Guojing Cong, Seung-Hwan Lim:
Versatile feature learning with graph convolutions and graph structures. ICDM (Workshops) 2021: 669-677 - [c41]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: 361-382 - 2020
- [j5]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): 2375-2391 (2020) - [c40]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: 272-281 - [c39]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: 27:1-27:11 - [c38]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: 180-190 - [c37]Moiz Arif, M. Mustafa Rafique, Seung-Hwan Lim, Zaki Malik:
Infrastructure-Aware TensorFlow for Heterogeneous Datacenters. MASCOTS 2020: 1-8 - [c36]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
2010 – 2019
- 2019
- [c35]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: 1488-1496 - [c34]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: 1-12 - [c33]Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim:
In-Place Zero-Space Memory Protection for CNN. NeurIPS 2019: 5735-5744 - [c32]Hui Guan, Xipeng Shen
, Seung-Hwan Lim:
Wootz: a compiler-based framework for fast CNN pruning via composability. PLDI 2019: 717-730 - [i2]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 abs/1909.12291 (2019) - [i1]Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim:
In-Place Zero-Space Memory Protection for CNN. CoRR abs/1910.14479 (2019) - 2018
- [c31]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: 718-723 - [c30]Luna Xu, Ali Raza Butt
, Seung-Hwan Lim, Ramakrishnan Kannan:
A Heterogeneity-Aware Task Scheduler for Spark. CLUSTER 2018: 245-256 - [c29]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: 50:1-50:11 - [c28]Randall Pittman, Hui Guan, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton:
Exploring flexible communications for streamlining DNN ensemble training pipelines. SC 2018: 64:1-64:12 - 2017
- [j4]Seung-Hwan Lim, Youngjae Kim:
A quantitative model of application slow-down in multi-resource shared systems. Perform. Evaluation 108: 32-47 (2017) - [c27]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: 273-282 - [c26]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: 5 - [c25]Seung-Hwan Lim, Hyogi Sim
, Raghul Gunasekaran, Sudharshan S. Vazhkudai:
Scientific user behavior and data-sharing trends in a petascale file system. SC 2017: 46 - 2016
- [j3]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: 9-25 (2016) - [c24]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: 1026-1031 - [c23]Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim:
Mini-apps for high performance data analysis. IEEE BigData 2016: 1483-1492 - [c22]John Harney, Seung-Hwan Lim, Sreenivas R. Sukumar, Dale Stansberry, Peter Xenopoulos:
On-demand data analytics in HPC environments at leadership computing facilities: Challenges and experiences. IEEE BigData 2016: 2087-2096 - [c21]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: 3052-3061 - [c20]Seokyong Hong, Sangkeun Lee, Seung-Hwan Lim, Sreenivas R. Sukumar, Ranga Raju Vatsavai:
Evaluation of Pattern Matching Workloads in Graph Analysis Systems. HPDC 2016: 263-266 - [c19]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: 25-30 - 2015
- [c18]Sangkeun Lee, Byung H. Park, Seung-Hwan Lim, Mallikarjun Shankar
:
Table2Graph: A Scalable Graph Construction from Relational Tables Using Map-Reduce. BigDataService 2015: 294-301 - [c17]Sangkeun Lee, Sreenivas R. Sukumar, Seung-Hwan Lim:
Graph mining meets the Semantic Web. ICDE Workshops 2015: 53-58 - [c16]Seung-Hwan Lim, Sangkeun Lee, Gautam Ganesh, Tyler C. Brown, Sreenivas R. Sukumar:
Graph Processing Platforms at Scale: Practices and Experiences. ISPASS 2015: 42-51 - [c15]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: 4:1-4:5 - 2014
- [c14]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: 885-893 - 2013
- [c13]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: 1001-1008 - 2012
- [c12]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: 1-8 - [c11]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: 129-140 - [c10]James L. Horey, Edmon Begoli, Raghul Gunasekaran, Seung-Hwan Lim, James J. Nutaro:
Big Data Platforms as a Service: Challenges and Approach. HotCloud 2012 - [c9]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: 271-282 - 2011
- [j2]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): 853-862 (2011) - [c8]Seung-Hwan Lim, Jae-Seok Huh, Youngjae Kim, Chita R. Das:
Migration, Assignment, and Scheduling of Jobs in Virtualized Environment. HotCloud 2011 - [c7]Seung-Hwan Lim, Bikash Sharma, Byung-Chul Tak, Chita R. Das:
A dynamic energy management scheme for multi-tier data centers. ISPASS 2011: 257-266 - [c6]Seung-Hwan Lim, Sang-Wook Kim, Soyoun Kim, Sanghyun Park:
Construction of a blog network based on information diffusion. SAC 2011: 937-941
2000 – 2009
- 2009
- [c5]Seung-Hwan Lim, Bikash Sharma, Gunwoo Nam, Eun-Kyoung Kim, Chita R. Das:
MDCSim: A multi-tier data center simulation, platform. CLUSTER 2009: 1-9 - [c4]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: 129-136 - [c3]Yong-Suk Kwon, Sang-Wook Kim, Sunju Park, Seung-Hwan Lim, Jae Bum Lee:
The information diffusion model in the blog world. SNAKDD 2009: 4 - [c2]Seung-Hwan Lim, Sang-Wook Kim, Sunju Park, Joon Ho Lee:
Determining content power users in a blog network. SNAKDD 2009: 5 - 2007
- [j1]Seung-Hwan Lim, Heejin Park, Sang-Wook Kim:
Using multiple indexes for efficient subsequence matching in time-series databases. Inf. Sci. 177(24): 5691-5706 (2007) - 2006
- [c1]Seung-Hwan Lim, Heejin Park, Sang-Wook Kim:
Using Multiple Indexes for Efficient Subsequence Matching in Time-Series Databases. DASFAA 2006: 65-79
Coauthor Index
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last updated on 2024-06-20 21:29 CEST by the dblp team
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