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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 2024-10-07 21:17 CEST by the dblp team
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