Guojing Cong

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 48

Top Topics

Graph Structure

Action Recognition

Distance Preserving

Top Venues

ICDM (Workshops)

Publications

Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa
Transductive Spiking Graph Neural Networks for Loihi. CoRR (2024)
Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony
Comparative Study of Large Language Model Architectures on Frontier. CoRR (2024)
Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony
Comparative Study of Large Language Model Architectures on Frontier. IPDPS (2024)
Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa
Transductive Spiking Graph Neural Networks for Loihi. ACM Great Lakes Symposium on VLSI (2024)
Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa
Exploration of Novel Neuromorphic Methodologies for Materials Applications. CoRR (2024)
Guojing Cong, Scott Auerbach
Clustering High-dimensional Toxicogenomics Data with Rare Signals. ICDM (Workshops) (2023)
Jiaji Ma, Guojing Cong, Scott Auerbach
Clustering and GNN prediction with DrugMatrix. BigData (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)
Yicong Zhu, Changnian Han, Peng Zhang, Guojing Cong, James R. Kozloski, Chih-Chieh Yang, Leili Zhang, Yuefan Deng
AI-aided multiscale modeling of physiologically-significant blood clots. Comput. Phys. Commun. 287 (2023)
Guojing Cong, Victor Fung
. Mach. Learn. Sci. Technol. 4 (3) (2023)
Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash
Optimizing Distributed Training on Frontier for Large Language Models. CoRR (2023)
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR (2023)
Changnian Han, Peng Zhang, Yicong Zhu, Guojing Cong, James R. Kozloski, Chih-Chieh Yang, Leili Zhang, Yuefan Deng
Scalable multiscale modeling of platelets with 100 million particles. J. Supercomput. 78 (18) (2022)
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)
Guojing Cong, Seung-Hwan Lim, Steven Young
Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning. ICDM (Workshops) (2022)
Guojing Cong, Anshul Gupta, Rodrigo Neumann, Maíra de Bayser, Mathias Steiner, Breanndán Ó Conchúir
Adsorption in Nano-Pores with Graph Neural Networks. CoRR (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)
Guojing Cong, Talia Ben-Naim, Victor Fung, Anshul Gupta, Rodrigo Neumann, Mathias Steiner
Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery. ICDM (Workshops) (2022)
Yicong Zhu, Changnian Han, Peng Zhang, Guojing Cong, James R. Kozloski, Chih-Chieh Yang, Leili Zhang, Yuefan Deng
AI-aided multiscale modeling of physiologically-significant blood clots. CoRR (2022)
Guojing Cong
Elastic distributed training with fast convergence and efficient resource utilization. ICMLA (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)
Changnian Han, Peng Zhang, Danny Bluestein, Guojing Cong, Yuefan Deng
Artificial intelligence for accelerating time integrations in multiscale modeling. J. Comput. Phys. 427 (2021)
Guojing Cong, Seung-Hwan Lim
Versatile feature learning with graph convolutions and graph structures. ICDM (Workshops) (2021)
Yicong Zhu, Peng Zhang, Changnian Han, Guojing Cong, Yuefan Deng
Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. ISC (2021)
Leili Zhang, Giacomo Domeniconi, Chih-Chieh Yang, Seung-gu Kang, Ruhong Zhou, Guojing Cong
CASTELO: clustered atom subtypes aided lead optimization - a combined machine learning and molecular modeling method. BMC Bioinform. 22 (1) (2021)
Guojing Cong, Tianyi Liu
Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum. CoRR (2021)
Guojing Cong, Tianyi Liu
Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum. MLHPC/AI4S@SC (2020)
Chih-Chieh Yang, Giacomo Domeniconi, Leili Zhang, Guojing Cong
Design of AI-Enhanced Drug Lead Optimization Workflow for HPC and Cloud. IEEE BigData (2020)
Guojing Cong, Brian Kingsbury, Chih-Chieh Yang, Tianyi Liu
Fast Training of Deep Neural Networks for Speech Recognition. ICASSP (2020)
Guojing Cong, Li Zhang, Chih-Chieh Yang
Partial data permutation for training deep neural networks. CCGRID (2020)
Leili Zhang, Giacomo Domeniconi, Chih-Chieh Yang, Seung-gu Kang, Ruhong Zhou, Guojing Cong
CASTELO: Clustered Atom Subtypes aidEd Lead Optimization - a combined machine learning and molecular modeling method. CoRR (2020)
Guojing Cong, Giacomo Domeniconi, Joshua Shapiro, Chih-Chieh Yang, Barry Chen
Video Action Recognition With an Additional End-to-End Trained Temporal Stream. WACV (2019)
Chih-Chieh Yang, Guojing Cong
Accelerating Data Loading in Deep Neural Network Training. HiPC (2019)
Chih-Chieh Yang, Guojing Cong
Accelerating Data Loading in Deep Neural Network Training. CoRR (2019)
Guojing Cong, Chih-Chieh Yang, Fan Zhou
Reducing global reductions in large-scale distributed training. ICPP Workshops (2019)
Ian Karlin, Yoonho Park, Bronis R. de Supinski, Peng Wang, Bert Still, David Beckingsale, Robert Blake, Tong Chen, Guojing Cong, Carlos H. A. Costa, Johann Dahm, Giacomo Domeniconi, Thomas Epperly, Aaron Fisher, Sara Kokkila Schumacher, Steven H. Langer, Hai Le, Eun Kyung Lee, Naoya Maruyama, Xinyu Que, David F. Richards, Björn Sjögreen, Jonathan Wong, Carol S. Woodward, Ulrike Meier Yang, Xiaohua Zhang, Bob Anderson, David Appelhans, Levi Barnes, Peter D. Barnes Jr., Sorin Bastea, David Böhme, Jamie A. Bramwell, James M. Brase, José R. Brunheroto, Barry Chen, Charway R. Cooper, Tony Degroot, Robert D. Falgout, Todd Gamblin, David J. Gardner, James N. Glosli, John A. Gunnels, Max P. Katz, Tzanio V. Kolev, I-Feng W. Kuo, Matthew P. LeGendre, Ruipeng Li, Pei-Hung Lin, Shelby Lockhart, Kathleen McCandless, Claudia Misale, Jaime H. Moreno, Rob Neely, Jarom Nelson, Rao Nimmakayala, Kathryn M. O'Brien, Kevin O'Brien, Ramesh Pankajakshan, Roger Pearce, Slaven Peles, Phil Regier, Steven C. Rennich, Martin Schulz, Howard Scott, James C. Sexton, Kathleen Shoga, Shiv Sundram, Guillaume Thomas-Collignon, Brian Van Essen, Alexey Voronin, Bob Walkup, Lu Wang, Chris Ward, Hui-Fang Wen, Daniel A. White, Christopher Young, Cyril Zeller, Edward Zywicz
Preparation and optimization of a diverse workload for a large-scale heterogeneous system. SC (2019)
Guojing Cong, Giacomo Domeniconi, Chih-Chieh Yang, Joshua Shapiro, Fan Zhou, Barry Chen
Fast neural network training on a cluster of GPUs for action recognition with high accuracy. J. Parallel Distributed Comput. 134 (2019)
Fan Zhou, Guojing Cong
A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction. CoRR (2019)
Fan Zhou, Guojing Cong
On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization. IJCAI (2018)
Guojing Cong, Giacomo Domeniconi, Joshua Shapiro, Fan Zhou, Barry Chen
Accelerating Deep Neural Network Training for Action Recognition on a Cluster of GPUs. SBAC-PAD (2018)
Fan Zhou, Guojing Cong
On the convergence properties of a K-step averaging stochastic gradient descent algorithm for nonconvex optimization. CoRR (2017)
Guojing Cong, Onkar Bhardwaj
A Hierarchical, Bulk-Synchronous Stochastic Gradient Descent Algorithm for Deep-Learning Applications on GPU Clusters. ICMLA (2017)
Christian Plessl, Guojing Cong, João M. P. Cardoso
Foreword to the special issue of the 18th IEEE international conference on computational science and engineering (CSE2015). Concurr. Comput. Pract. Exp. 29 (7) (2017)
Guojing Cong, Onkar Bhardwaj, Minwei Feng
An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications. ICPP (2017)
Guojing Cong, Brian Kingsbury, Soumyadip Gosh, George Saon, Fan Zhou
Accelerating deep neural network learning for speech recognition on a cluster of GPUs. MLHPC@SC (2017)
Guojing Cong, Ilie Gabriel Tanase
Composable Locality Optimizations for Accelerating Parallel Forest Computations. HPCC/SmartCity/DSS (2016)
Onkar Bhardwaj, Guojing Cong
Practical Efficiency of Asynchronous Stochastic Gradient Descent. MLHPC@SC (2016)
Guojing Cong, Carol Meyers, Deepak Rajan, Tiziano Parriani
Parallel Strategies for Solving Large Unit Commitment Problems in the California ISO Planning Model. IPDPS (2015)
Kattamuri Ekanadham, Guojing Cong
Memory Centric Computation (Mc2) for Large-Scale Graph Processing. SBAC-PAD (2015)
Guojing Cong, Sophia Wen, James Sedgwick, Louis Ly
Parallelism-centric optimization and performance study of a finance aggregation engine on modern NUMA systems. WHPCF@SC (2015)
Guojing Cong, Ilie Gabriel Tanase, Yinglong Xia
Accelerating Minimum Spanning Forest Computations on Multicore Platforms. Euro-Par Workshops (2015)
Guojing Cong
A Synchronous Parallel Max-Flow Algorithm for Real-World Networks. HPCC/CSS/ICESS (2014)
Guojing Cong, Paul Muzio
Fast Parallel Connected Components Algorithms on GPUs. Euro-Par Workshops (1) (2014)
Guojing Cong, Hui-Fang Wen
Maximizing the performance of irregular applications on multithreaded, NUMA systems. IA3@SC (2013)
Guojing Cong, Hui-Fang Wen
Mapping applications for high performance on multithreaded, NUMA systems. Conf. Computing Frontiers (2013)
Guojing Cong, Hui-Fang Wen, Hiroki Murata, Yasushi Negishi
Tool-assisted Optimization of Shared-memory Accesses in UPC Applications. HPCC-ICESS (2012)
Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama
A Systematic Approach toward Automated Performance Analysis and Tuning. IEEE Trans. Parallel Distributed Syst. 23 (3) (2012)
Guojing Cong, Hui-Fang Wen, I-Hsin Chung, David J. Klepacki, Hiroki Murata, Yasushi Negishi
An Efficient Framework for Multi-dimensional Tuning of High Performance Computing Applications. IPDPS (2012)
Guojing Cong, Konstantin Makarychev
Optimizing Large-scale Graph Analysis on Multithreaded, Multicore Platforms. IPDPS (2012)
Yasushi Negishi, Hiroki Murata, Guojing Cong, Hui-Fang Wen, I-Hsin Chung
A static analysis tool using a three-step approach for data races in HPC programs. PADTAD (2012)
I-Hsin Chung, Changhoan Kim, Hui-Fang Wen, Guojing Cong
Application data prefetching on the IBM blue gene/Q supercomputer. SC (2012)
Guojing Cong, Konstantin Makarychev
Optimizing Large-Scale Graph Analysis on a Multi-threaded, Multi-core Platform. IPDPS (2011)
Seetharami Seelam, I-Hsin Chung, Guojing Cong, Hui-Fang Wen, David J. Klepacki
Workload performance characterization of DARPA HPCS benchmarks. Concurr. Comput. Pract. Exp. 22 (4) (2010)
Guojing Cong, George Almási, Vijay A. Saraswat
Fast PGAS Implementation of Distributed Graph Algorithms. SC (2010)
Judit Giménez, Jesús Labarta, F. Xavier Pegenaute, Hui-Fang Wen, David J. Klepacki, I-Hsin Chung, Guojing Cong, Felix Voigtländer, Bernd Mohr
Guided Performance Analysis Combining Profile and Trace Tools. Euro-Par Workshops (2010)
Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama
Application tuning through bottleneck-driven refactoring. IPDPS Workshops (2010)
Guojing Cong, Seetharami Seelam, I-Hsin Chung, Sophia Wen, David J. Klepacki
Towards a framework for automated performance tuning. IPDPS (2009)
Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama
A Holistic Approach towards Automated Performance Analysis and Tuning. Euro-Par (2009)
Guojing Cong, Konstantin Makarychev
Improving Memory Access Locality for Large-Scale Graph Analysis Applications. PDCCS (2009)
Guojing Cong, Hanhong Xue
A scalable, asynchronous spanning tree algorithm on a cluster of SMPs. IPDPS (2008)
Guojing Cong, Sreedhar B. Kodali, Sriram Krishnamoorthy, Doug Lea, Vijay A. Saraswat, Tong Wen
Solving Large, Irregular Graph Problems Using Adaptive Work-Stealing. ICPP (2008)
I-Hsin Chung, Guojing Cong, David J. Klepacki, Simone Sbaraglia, Seetharami Seelam, Hui-Fang Wen
A framework for automated performance bottleneck detection. IPDPS (2008)
Seetharami Seelam, I-Hsin Chung, Guojing Cong, Hui-Fang Wen, David J. Klepacki
Workload Performance Characterization of DARPA HPCS Benchmarks. HPCC (2008)
Hui-Fang Wen, Simone Sbaraglia, Seetharami Seelam, I-Hsin Chung, Guojing Cong, David J. Klepacki
A Productivity Centered Tools Framework for Application Performance Tuning. QEST (2007)
Simone Sbaraglia, Hui-Fang Wen, Seetharami Seelam, I-Hsin Chung, Guojing Cong, Kattamuri Ekanadham, David J. Klepacki
A productivity centered application performance tuning framework. VALUETOOLS (2007)
Guojing Cong, David A. Bader
Techniques for Designing Efficient Parallel Graph Algorithms for SMPs and Multicore Processors. ISPA (2007)
Abhinav Bhatele, Guojing Cong
A Selective Pro ling Tool: Towards Automatic Performance Tuning. IPDPS (2007)
Guojing Cong, David A. Bader
Designing irregular parallel algorithms with mutual exclusion and lock-free protocols. J. Parallel Distributed Comput. 66 (6) (2006)
Guojing Cong, Simone Sbaraglia
A Study on the Locality Behavior of Minimum Spanning Tree Algorithms. HiPC (2006)
David A. Bader, Guojing Cong
Fast shared-memory algorithms for computing the minimum spanning forest of sparse graphs. J. Parallel Distributed Comput. 66 (11) (2006)
Guojing Cong, David A. Bader
An Experimental Study of Parallel Biconnected Components Algorithms on Symmetric Multiprocessors (SMPs). IPDPS (2005)
David A. Bader, Guojing Cong, John Feo
On the Architectural Requirements for Efficient Execution of Graph Algorithms. ICPP (2005)
Guojing Cong, David A. Bader
An Empirical Analysis of Parallel Random Permutation Algorithms ON SMPs. PDCS (2005)
David A. Bader, Guojing Cong
A fast, parallel spanning tree algorithm for symmetric multiprocessors (SMPs). J. Parallel Distributed Comput. 65 (9) (2005)
David A. Bader, Guojing Cong
A Fast, Parallel Spanning Tree Algorithm for Symmetric Multiprocessors. IPDPS (2004)
Guojing Cong, David A. Bader
Lock-Free Parallel Algorithms: An Experimental Study. HiPC (2004)
David A. Bader, Guojing Cong
Fast Shared-Memory Algorithms for Computing the Minimum Spanning Forest of Sparse Graphs. IPDPS (2004)
Guojing Cong, David A. Bader
The Euler Tour Technique and Parallel Rooted Spanning Tree. ICPP (2004)