Guojing Cong - RankMe

105 papers A* 1A 17B 6C 10Misc 4Journal 29Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Transplatformer: translating toxicogenomic profiles between generations of platforms. BMC Bioinform. Guojing Cong, Robert M. Patton, Frank Chao, Daniel L. Svoboda, Jeremy N. Erickson, Michele R. Balik-Meisner, Deepak Mav, Dhiral P. Phadke, Elizabeth H. Scholl, Ruchir R. Shah, Scott S. Auerbach
2025	J	`jnl`	Completion of the DrugMatrix Toxicogenomics Database using 3-Dimensional Tensors. CoRR Tan Nguyen, Guojing Cong
2025	J	`jnl`	HyperGraphX: Graph Transductive Learning with Hyperdimensional Computing and Message Passing. CoRR Guojing Cong, Thomas E. Potok, Hamed Poursiami, Maryam Parsa
2025	J	`jnl`	VS-Graph: Scalable and Efficient Graph Classification Using Hyperdimensional Computing. CoRR Hamed Poursiami, Shay Snyder, Guojing Cong, Thomas E. Potok, Maryam Parsa
2024	A	`conf`	Comparative Study of Large Language Model Architectures on Frontier. IPDPS Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony
2024	J	`jnl`	Comparative Study of Large Language Model Architectures on Frontier. CoRR Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony
2024	—	`conf`	Cross-tissue, Cross-platform Prediction and Validation of Toxicogenomics Profiles with Deep Learning and Clustering. ICDM (Workshops) Trang Do, Richard Kim, Scott Auerbach, Warren M. Casey, Andrew A. Rooney, Guojing Cong
2024	—	`conf`	Exploration of Novel Neuromorphic Methodologies for Materials Applications. ICONS Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa
2024	J	`jnl`	Exploration of Novel Neuromorphic Methodologies for Materials Applications. CoRR Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa
2024	C	`conf`	Optimizing Distributed Training on Frontier for Large Language Models. ISC Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, J. Austin Ellis, Matthias Maiterth, Guojing Cong, Feiyi Wang, Prasanna Balaprakash
2024	C	`conf`	Predicting Drug Effects from High-Dimensional, Asymmetric Drug Datasets by Using Graph Neural Networks: A Comprehensive Analysis of Multitarget Drug Effect Prediction. ICMLA Avishek Bose, Guojing Cong
2024	J	`jnl`	Predicting Drug Effects from High-Dimensional, Asymmetric Drug Datasets by Using Graph Neural Networks: A Comprehensive Analysis of Multitarget Drug Effect Prediction. CoRR Avishek Bose, Guojing Cong
2024	—	`conf`	Transductive Spiking Graph Neural Networks for Loihi. ACM Great Lakes Symposium on VLSI Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa
2024	J	`jnl`	Transductive Spiking Graph Neural Networks for Loihi. CoRR Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa
2023	J	`jnl`	AI-aided multiscale modeling of physiologically-significant blood clots. Comput. Phys. Commun. Yicong Zhu, Changnian Han, Peng Zhang, Guojing Cong, James R. Kozloski, Chih-Chieh Yang, Leili Zhang, Yuefan Deng
2023	—	`conf`	Clustering High-dimensional Toxicogenomics Data with Rare Signals. ICDM (Workshops) Guojing Cong, Scott Auerbach
2023	B	`conf`	Clustering and GNN prediction with DrugMatrix. IEEE Big Data Jiaji Ma, Guojing Cong, Scott Auerbach
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR 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 W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	C	`conf`	Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. ICMLA Guojing Cong, Shruti R. Kulkarni, Seung-Hwan Lim, Prasanna Date, Shay Snyder, Maryam Parsa, Dominic Kennedy, Catherine D. Schuman
2023	J	`jnl`	Improving materials property predictions for graph neural networks with minimal feature engineering Mach. Learn. Sci. Technol. Guojing Cong, Victor Fung
2023	J	`jnl`	Optimizing Distributed Training on Frontier for Large Language Models. CoRR Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash
2022	J	`jnl`	AI-aided multiscale modeling of physiologically-significant blood clots. CoRR Yicong Zhu, Changnian Han, Peng Zhang, Guojing Cong, James R. Kozloski, Chih-Chieh Yang, Leili Zhang, Yuefan Deng
2022	—	`conf`	Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning. ICDM (Workshops) Guojing Cong, Seung-Hwan Lim, Steven Young
2022	A	`conf`	Exaflops Biomedical Knowledge Graph Analytics. SC 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
2022	—	`conf`	Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery. ICDM (Workshops) Guojing Cong, Talia Ben-Naim, Victor Fung, Anshul Gupta, Rodrigo Neumann, Mathias Steiner
2022	—	`conf`	Neuromorphic Computing for Scientific Applications. RSDHA@SC 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
2022	J	`jnl`	Prediction of CO CoRR Guojing Cong, Anshul Gupta, Rodrigo Neumann, Maíra de Bayser, Mathias Steiner, Breanndán Ó Conchúir
2022	J	`jnl`	Scalable multiscale modeling of platelets with 100 million particles. J. Supercomput. Changnian Han, Peng Zhang, Yicong Zhu, Guojing Cong, James R. Kozloski, Chih-Chieh Yang, Leili Zhang, Yuefan Deng
2022	—	`conf`	Semi-Supervised Graph Structure Learning on Neuromorphic Computers. ICONS Guojing Cong, Seung-Hwan Lim, Shruti R. Kulkarni, Prasanna Date, Thomas E. Potok, Shay Snyder, Maryam Parsa, Catherine D. Schuman
2021	J	`jnl`	Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum. CoRR Guojing Cong, Tianyi Liu
2021	J	`jnl`	Artificial intelligence for accelerating time integrations in multiscale modeling. J. Comput. Phys. Changnian Han, Peng Zhang, Danny Bluestein, Guojing Cong, Yuefan Deng
2021	J	`jnl`	CASTELO: clustered atom subtypes aided lead optimization - a combined machine learning and molecular modeling method. BMC Bioinform. Leili Zhang, Giacomo Domeniconi, Chih-Chieh Yang, Seung-gu Kang, Ruhong Zhou, Guojing Cong
2021	C	`conf`	Elastic distributed training with fast convergence and efficient resource utilization. ICMLA Guojing Cong
2021	C	`conf`	Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. ISC Yicong Zhu, Peng Zhang, Changnian Han, Guojing Cong, Yuefan Deng
2021	—	`conf`	Versatile feature learning with graph convolutions and graph structures. ICDM (Workshops) Guojing Cong, Seung-Hwan Lim
2021	—	`conf`	Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis. IEEE BigData Seung-Hwan Lim, Junghoon Chae, Guojing Cong, Drahomira Herrmannova, Robert M. Patton, Ramakrishnan Kannan, Thomas E. Potok
2020	—	`conf`	Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum. MLHPC/AI4S@SC Guojing Cong, Tianyi Liu
2020	J	`jnl`	CASTELO: Clustered Atom Subtypes aidEd Lead Optimization - a combined machine learning and molecular modeling method. CoRR Leili Zhang, Giacomo Domeniconi, Chih-Chieh Yang, Seung-gu Kang, Ruhong Zhou, Guojing Cong
2020	—	`conf`	Design of AI-Enhanced Drug Lead Optimization Workflow for HPC and Cloud. IEEE BigData Chih-Chieh Yang, Giacomo Domeniconi, Leili Zhang, Guojing Cong
2020	Misc	`conf`	Fast Training of Deep Neural Networks for Speech Recognition. ICASSP Guojing Cong, Brian Kingsbury, Chih-Chieh Yang, Tianyi Liu
2020	B	`conf`	Partial data permutation for training deep neural networks. CCGRID Guojing Cong, Li Zhang, Chih-Chieh Yang
2019	J	`jnl`	A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction. CoRR Fan Zhou, Guojing Cong
2019	Misc	`conf`	Accelerating Data Loading in Deep Neural Network Training. HiPC Chih-Chieh Yang, Guojing Cong
2019	J	`jnl`	Accelerating Data Loading in Deep Neural Network Training. CoRR Chih-Chieh Yang, Guojing Cong
2019	J	`jnl`	Fast neural network training on a cluster of GPUs for action recognition with high accuracy. J. Parallel Distributed Comput. Guojing Cong, Giacomo Domeniconi, Chih-Chieh Yang, Joshua Shapiro, Fan Zhou, Barry Chen
2019	A	`conf`	Preparation and optimization of a diverse workload for a large-scale heterogeneous system. SC 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
2019	—	`conf`	Reducing global reductions in large-scale distributed training. ICPP Workshops Guojing Cong, Chih-Chieh Yang, Fan Zhou
2019	A	`conf`	Video Action Recognition With an Additional End-to-End Trained Temporal Stream. WACV Guojing Cong, Giacomo Domeniconi, Joshua Shapiro, Chih-Chieh Yang, Barry Chen
2018	C	`conf`	Accelerating Deep Neural Network Training for Action Recognition on a Cluster of GPUs. SBAC-PAD Guojing Cong, Giacomo Domeniconi, Joshua Shapiro, Fan Zhou, Barry Chen
2018	A*	`conf`	On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization. IJCAI Fan Zhou, Guojing Cong
2017	C	`conf`	A Hierarchical, Bulk-Synchronous Stochastic Gradient Descent Algorithm for Deep-Learning Applications on GPU Clusters. ICMLA Guojing Cong, Onkar Bhardwaj
2017	—	`conf`	Accelerating deep neural network learning for speech recognition on a cluster of GPUs. MLHPC@SC Guojing Cong, Brian Kingsbury, Soumyadip Gosh, George Saon, Fan Zhou
2017	B	`conf`	An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications. ICPP Guojing Cong, Onkar Bhardwaj, Minwei Feng
2017	J	`jnl`	Foreword to the special issue of the 18th IEEE international conference on computational science and engineering (CSE2015). Concurr. Comput. Pract. Exp. Christian Plessl, Guojing Cong, João M. P. Cardoso
2017	J	`jnl`	On the convergence properties of a K-step averaging stochastic gradient descent algorithm for nonconvex optimization. CoRR Fan Zhou, Guojing Cong
2016	—	`conf`	Composable Locality Optimizations for Accelerating Parallel Forest Computations. HPCC/SmartCity/DSS Guojing Cong, Ilie Gabriel Tanase
2016	—	`conf`	Practical Efficiency of Asynchronous Stochastic Gradient Descent. MLHPC@SC Onkar Bhardwaj, Guojing Cong
2015	—	`ed.`	18th IEEE International Conference on Computational Science and Engineering, CSE 2015, Porto, Portugal, October 21-23, 2015 CSE Christian Plessl, Didier El Baz, Guojing Cong, João M. P. Cardoso, Luís Veiga, Thomas Rauber
2015	—	`conf`	Accelerating Minimum Spanning Forest Computations on Multicore Platforms. Euro-Par Workshops Guojing Cong, Ilie Gabriel Tanase, Yinglong Xia
2015	C	`conf`	Memory Centric Computation (Mc2) for Large-Scale Graph Processing. SBAC-PAD Kattamuri Ekanadham, Guojing Cong
2015	A	`conf`	Parallel Strategies for Solving Large Unit Commitment Problems in the California ISO Planning Model. IPDPS Guojing Cong, Carol Meyers, Deepak Rajan, Tiziano Parriani
2015	—	`conf`	Parallelism-centric optimization and performance study of a finance aggregation engine on modern NUMA systems. WHPCF@SC Guojing Cong, Sophia Wen, James Sedgwick, Louis Ly
2014	—	`conf`	A Synchronous Parallel Max-Flow Algorithm for Real-World Networks. HPCC/CSS/ICESS Guojing Cong
2014	—	`conf`	Fast Parallel Connected Components Algorithms on GPUs. Euro-Par Workshops (1) Guojing Cong, Paul Muzio
2013	—	`conf`	Mapping applications for high performance on multithreaded, NUMA systems. Conf. Computing Frontiers Guojing Cong, Hui-Fang Wen
2013	—	`conf`	Maximizing the performance of irregular applications on multithreaded, NUMA systems. IA3@SC Guojing Cong, Hui-Fang Wen
2012	J	`jnl`	A Systematic Approach toward Automated Performance Analysis and Tuning. IEEE Trans. Parallel Distributed Syst. Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama
2012	—	`conf`	A static analysis tool using a three-step approach for data races in HPC programs. PADTAD Yasushi Negishi, Hiroki Murata, Guojing Cong, Hui-Fang Wen, I-Hsin Chung
2012	A	`conf`	An Efficient Framework for Multi-dimensional Tuning of High Performance Computing Applications. IPDPS Guojing Cong, Hui-Fang Wen, I-Hsin Chung, David J. Klepacki, Hiroki Murata, Yasushi Negishi
2012	A	`conf`	Application data prefetching on the IBM blue gene/Q supercomputer. SC I-Hsin Chung, Changhoan Kim, Hui-Fang Wen, Guojing Cong
2012	A	`conf`	Optimizing Large-scale Graph Analysis on Multithreaded, Multicore Platforms. IPDPS Guojing Cong, Konstantin Makarychev
2012	—	`conf`	Tool-assisted Optimization of Shared-memory Accesses in UPC Applications. HPCC-ICESS Guojing Cong, Hui-Fang Wen, Hiroki Murata, Yasushi Negishi
2011	—	`ch.`	Graph Algorithms. Encyclopedia of Parallel Computing David A. Bader, Guojing Cong
2011	—	`ch.`	Hybrid Programming With SIMPLE. Encyclopedia of Parallel Computing Guojing Cong, David A. Bader
2011	A	`conf`	Optimizing Large-Scale Graph Analysis on a Multi-threaded, Multi-core Platform. IPDPS Guojing Cong, Konstantin Makarychev
2011	—	`ch.`	SWARM: A Parallel Programming Framework for Multicore Processors. Encyclopedia of Parallel Computing David A. Bader, Guojing Cong
2011	—	`ch.`	Spanning Tree, Minimum Weight. Encyclopedia of Parallel Computing David A. Bader, Guojing Cong
2010	—	`conf`	Application tuning through bottleneck-driven refactoring. IPDPS Workshops Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama
2010	A	`conf`	Fast PGAS Implementation of Distributed Graph Algorithms. SC Guojing Cong, George Almási, Vijay A. Saraswat
2010	—	`conf`	Guided Performance Analysis Combining Profile and Trace Tools. Euro-Par Workshops Judit Giménez, Jesús Labarta, F. Xavier Pegenaute, Hui-Fang Wen, David J. Klepacki, I-Hsin Chung, Guojing Cong, Felix Voigtländer, Bernd Mohr
2010	J	`jnl`	Workload performance characterization of DARPA HPCS benchmarks. Concurr. Comput. Pract. Exp. Seetharami R. Seelam, I-Hsin Chung, Guojing Cong, Hui-Fang Wen, David J. Klepacki
2009	—	`conf`	A Holistic Approach towards Automated Performance Analysis and Tuning. Euro-Par Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama
2009	—	`conf`	Improving Memory Access Locality for Large-Scale Graph Analysis Applications. PDCCS Guojing Cong, Konstantin Makarychev
2009	A	`conf`	Towards a framework for automated performance tuning. IPDPS Guojing Cong, Seetharami R. Seelam, I-Hsin Chung, Sophia Wen, David J. Klepacki
2008	A	`conf`	A framework for automated performance bottleneck detection. IPDPS I-Hsin Chung, Guojing Cong, David J. Klepacki, Simone Sbaraglia, Seetharami R. Seelam, Hui-Fang Wen
2008	A	`conf`	A scalable, asynchronous spanning tree algorithm on a cluster of SMPs. IPDPS Guojing Cong, Hanhong Xue
2008	B	`conf`	Solving Large, Irregular Graph Problems Using Adaptive Work-Stealing. ICPP Guojing Cong, Sreedhar B. Kodali, Sriram Krishnamoorthy, Doug Lea, Vijay A. Saraswat, Tong Wen
2008	C	`conf`	Workload Performance Characterization of DARPA HPCS Benchmarks. HPCC Seetharami R. Seelam, I-Hsin Chung, Guojing Cong, Hui-Fang Wen, David J. Klepacki
2007	—	`conf`	A Productivity Centered Tools Framework for Application Performance Tuning. QEST Hui-Fang Wen, Simone Sbaraglia, Seetharami R. Seelam, I-Hsin Chung, Guojing Cong, David J. Klepacki
2007	A	`conf`	A Selective Pro ling Tool: Towards Automatic Performance Tuning. IPDPS Abhinav Bhatele, Guojing Cong
2007	—	`conf`	A productivity centered application performance tuning framework. VALUETOOLS Simone Sbaraglia, Hui-Fang Wen, Seetharami R. Seelam, I-Hsin Chung, Guojing Cong, Kattamuri Ekanadham, David J. Klepacki
2007	—	`ch.`	Design of Multithreaded Algorithms for Combinatorial Problems. Handbook of Parallel Computing Kamesh Madduri, John Feo, Guojing Cong, David A. Bader
2007	—	`ch.`	Efficient Parallel Graph Algorithms for Multicore and Multiprocessors. Handbook of Parallel Computing Guojing Cong, David A. Bader
2007	C	`conf`	Techniques for Designing Efficient Parallel Graph Algorithms for SMPs and Multicore Processors. ISPA Guojing Cong, David A. Bader
2006	Misc	`conf`	A Study on the Locality Behavior of Minimum Spanning Tree Algorithms. HiPC Guojing Cong, Simone Sbaraglia
2006	J	`jnl`	Designing irregular parallel algorithms with mutual exclusion and lock-free protocols. J. Parallel Distributed Comput. Guojing Cong, David A. Bader
2006	J	`jnl`	Fast shared-memory algorithms for computing the minimum spanning forest of sparse graphs. J. Parallel Distributed Comput. David A. Bader, Guojing Cong
2005	J	`jnl`	A fast, parallel spanning tree algorithm for symmetric multiprocessors (SMPs). J. Parallel Distributed Comput. David A. Bader, Guojing Cong
2005	—	`conf`	An Empirical Analysis of Parallel Random Permutation Algorithms ON SMPs. PDCS Guojing Cong, David A. Bader
2005	A	`conf`	An Experimental Study of Parallel Biconnected Components Algorithms on Symmetric Multiprocessors (SMPs). IPDPS Guojing Cong, David A. Bader
2005	B	`conf`	On the Architectural Requirements for Efficient Execution of Graph Algorithms. ICPP David A. Bader, Guojing Cong, John Feo
2004	A	`conf`	A Fast, Parallel Spanning Tree Algorithm for Symmetric Multiprocessors. IPDPS David A. Bader, Guojing Cong
2004	A	`conf`	Fast Shared-Memory Algorithms for Computing the Minimum Spanning Forest of Sparse Graphs. IPDPS David A. Bader, Guojing Cong
2004	Misc	`conf`	Lock-Free Parallel Algorithms: An Experimental Study. HiPC Guojing Cong, David A. Bader
2004	B	`conf`	The Euler Tour Technique and Parallel Rooted Spanning Tree. ICPP Guojing Cong, David A. Bader