Lock-Free Parallel Algorithms: An Experimental Study. - Guojing Cong; David A. Bader (HiPC, 2004)

The Euler Tour Technique and Parallel Rooted Spanning Tree. - Guojing Cong; David A. Bader (ICPP, 2004)

A Fast, Parallel Spanning Tree Algorithm for Symmetric Multiprocessors. - David A. Bader; Guojing Cong (IPDPS, 2004)

An Empirical Analysis of Parallel Random Permutation Algorithms ON SMPs. - Guojing Cong; David A. Bader (PDCS, 2005)

On the Architectural Requirements for Efficient Execution of Graph Algorithms. - David A. Bader; Guojing Cong; John Feo (ICPP, 2005)

An Experimental Study of Parallel Biconnected Components Algorithms on Symmetric Multiprocessors (SMPs). - Guojing Cong; David A. Bader (IPDPS, 2005)

A fast, parallel spanning tree algorithm for symmetric multiprocessors (SMPs). - David A. Bader; Guojing Cong (J. Parallel Distributed Comput., 2005)

A Study on the Locality Behavior of Minimum Spanning Tree Algorithms. - Guojing Cong; Simone Sbaraglia (HiPC, 2006)

Fast shared-memory algorithms for computing the minimum spanning forest of sparse graphs. - David A. Bader; Guojing Cong (J. Parallel Distributed Comput., 2006)

Designing irregular parallel algorithms with mutual exclusion and lock-free protocols. - Guojing Cong; David A. Bader (J. Parallel Distributed Comput., 2006)

A Selective Pro ling Tool: Towards Automatic Performance Tuning. - Abhinav Bhatele; Guojing Cong (IPDPS, 2007)

Techniques for Designing Efficient Parallel Graph Algorithms for SMPs and Multicore Processors. - Guojing Cong; David A. Bader (ISPA, 2007)

A Productivity Centered Tools Framework for Application Performance Tuning. - Hui-Fang Wen; Simone Sbaraglia; Seetharami R. Seelam; I-Hsin Chung; Guojing Cong; David J. Klepacki (QEST, 2007)

A productivity centered application performance tuning framework. - Simone Sbaraglia; Hui-Fang Wen; Seetharami R. Seelam; I-Hsin Chung; Guojing Cong; Kattamuri Ekanadham; David J. Klepacki (VALUETOOLS, 2007)

Efficient Parallel Graph Algorithms for Multicore and Multiprocessors. - Guojing Cong; David A. Bader (Handbook of Parallel Computing, 2007)

Design of Multithreaded Algorithms for Combinatorial Problems. - Kamesh Madduri; John Feo; Guojing Cong; David A. Bader (Handbook of Parallel Computing, 2007)

Solving Large, Irregular Graph Problems Using Adaptive Work-Stealing. - Guojing Cong; Sreedhar B. Kodali; Sriram Krishnamoorthy; Doug Lea; Vijay A. Saraswat; Tong Wen (ICPP, 2008)

A framework for automated performance bottleneck detection. - I-Hsin Chung; Guojing Cong; David J. Klepacki; Simone Sbaraglia; Seetharami R. Seelam; Hui-Fang Wen (IPDPS, 2008)

A scalable, asynchronous spanning tree algorithm on a cluster of SMPs. - Guojing Cong; Hanhong Xue (IPDPS, 2008)

Improving Memory Access Locality for Large-Scale Graph Analysis Applications. - Guojing Cong; Konstantin Makarychev (PDCCS, 2009)

A Holistic Approach towards Automated Performance Analysis and Tuning. - Guojing Cong; I-Hsin Chung; Hui-Fang Wen; David J. Klepacki; Hiroki Murata; Yasushi Negishi; Takao Moriyama (Euro-Par, 2009)

Towards a framework for automated performance tuning. - Guojing Cong; Seetharami R. Seelam; I-Hsin Chung; Sophia Wen; David J. Klepacki (IPDPS, 2009)

Guided Performance Analysis Combining Profile and Trace Tools. - Judit Giménez; Jesús Labarta; F. Xavier Pegenaute; Hui-Fang Wen; David J. Klepacki; I-Hsin Chung; Guojing Cong; Felix Voigtländer; Bernd Mohr (Euro-Par Workshops, 2010)

Application tuning through bottleneck-driven refactoring. - Guojing Cong; I-Hsin Chung; Hui-Fang Wen; David J. Klepacki; Hiroki Murata; Yasushi Negishi; Takao Moriyama (IPDPS Workshops, 2010)

Fast PGAS Implementation of Distributed Graph Algorithms. - Guojing Cong; George Almási 001; Vijay A. Saraswat (SC, 2010)

Workload performance characterization of DARPA HPCS benchmarks. - Seetharami R. Seelam; I-Hsin Chung; Guojing Cong; Hui-Fang Wen; David J. Klepacki (Concurr. Comput. Pract. Exp., 2010)

Optimizing Large-Scale Graph Analysis on a Multi-threaded, Multi-core Platform. - Guojing Cong; Konstantin Makarychev (IPDPS, 2011)

Graph Algorithms. - David A. Bader; Guojing Cong (Encyclopedia of Parallel Computing, 2011)

Spanning Tree, Minimum Weight. - David A. Bader; Guojing Cong (Encyclopedia of Parallel Computing, 2011)

SWARM: A Parallel Programming Framework for Multicore Processors. - David A. Bader; Guojing Cong (Encyclopedia of Parallel Computing, 2011)

Hybrid Programming With SIMPLE. - Guojing Cong; David A. Bader (Encyclopedia of Parallel Computing, 2011)

Tool-assisted Optimization of Shared-memory Accesses in UPC Applications. - Guojing Cong; Hui-Fang Wen; Hiroki Murata; Yasushi Negishi (HPCC-ICESS, 2012)

Optimizing Large-scale Graph Analysis on Multithreaded, Multicore Platforms. - Guojing Cong; Konstantin Makarychev (IPDPS, 2012)

An Efficient Framework for Multi-dimensional Tuning of High Performance Computing Applications. - Guojing Cong; Hui-Fang Wen; I-Hsin Chung; David J. Klepacki; Hiroki Murata; Yasushi Negishi (IPDPS, 2012)

A static analysis tool using a three-step approach for data races in HPC programs. - Yasushi Negishi; Hiroki Murata; Guojing Cong; Hui-Fang Wen; I-Hsin Chung (PADTAD, 2012)

Application data prefetching on the IBM blue gene/Q supercomputer. - I-Hsin Chung; Changhoan Kim; Hui-Fang Wen; Guojing Cong (SC, 2012)

A Systematic Approach toward Automated Performance Analysis and Tuning. - Guojing Cong; I-Hsin Chung; Hui-Fang Wen; David J. Klepacki; Hiroki Murata; Yasushi Negishi; Takao Moriyama (IEEE Trans. Parallel Distributed Syst., 2012)

Mapping applications for high performance on multithreaded, NUMA systems. - Guojing Cong; Hui-Fang Wen (Conf. Computing Frontiers, 2013)

Maximizing the performance of irregular applications on multithreaded, NUMA systems. - Guojing Cong; Hui-Fang Wen (IA3@SC, 2013)

Fast Parallel Connected Components Algorithms on GPUs. - Guojing Cong; Paul Muzio (Euro-Par Workshops (1), 2014)

A Synchronous Parallel Max-Flow Algorithm for Real-World Networks. - Guojing Cong (HPCC/CSS/ICESS, 2014)

Accelerating Minimum Spanning Forest Computations on Multicore Platforms. - Guojing Cong; Ilie Gabriel Tanase; Yinglong Xia (Euro-Par Workshops, 2015)

Parallel Strategies for Solving Large Unit Commitment Problems in the California ISO Planning Model. - Guojing Cong; Carol Meyers; Deepak Rajan; Tiziano Parriani (IPDPS, 2015)

Memory Centric Computation (Mc2) for Large-Scale Graph Processing. - Kattamuri Ekanadham; Guojing Cong (SBAC-PAD, 2015)

Parallelism-centric optimization and performance study of a finance aggregation engine on modern NUMA systems. - Guojing Cong; Sophia Wen; James Sedgwick; Louis Ly (WHPCF@SC, 2015)

Composable Locality Optimizations for Accelerating Parallel Forest Computations. - Guojing Cong; Ilie Gabriel Tanase (HPCC/SmartCity/DSS, 2016)

Practical Efficiency of Asynchronous Stochastic Gradient Descent. - Onkar Bhardwaj; Guojing Cong (MLHPC@SC, 2016)

A Hierarchical, Bulk-Synchronous Stochastic Gradient Descent Algorithm for Deep-Learning Applications on GPU Clusters. - Guojing Cong; Onkar Bhardwaj (ICMLA, 2017)

An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications. - Guojing Cong; Onkar Bhardwaj; Minwei Feng (ICPP, 2017)

Accelerating deep neural network learning for speech recognition on a cluster of GPUs. - Guojing Cong; Brian Kingsbury; Soumyadip Gosh; George Saon; Fan Zhou 010 (MLHPC@SC, 2017)

Foreword to the special issue of the 18th IEEE international conference on computational science and engineering (CSE2015). - Christian Plessl; Guojing Cong; João M. P. Cardoso (Concurr. Comput. Pract. Exp., 2017)

On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization. - Fan Zhou 010; Guojing Cong (IJCAI, 2018)

Accelerating Deep Neural Network Training for Action Recognition on a Cluster of GPUs. - Guojing Cong; Giacomo Domeniconi; Joshua Shapiro; Fan Zhou 010; Barry Chen (SBAC-PAD, 2018)

Accelerating Data Loading in Deep Neural Network Training. - Chih-Chieh Yang; Guojing Cong (HiPC, 2019)

Reducing global reductions in large-scale distributed training. - Guojing Cong; Chih-Chieh Yang; Fan Zhou 010 (ICPP Workshops, 2019)

Preparation and optimization of a diverse workload for a large-scale heterogeneous system. - Ian Karlin; Yoonho Park; Bronis R. de Supinski; Peng Wang; Bert Still; David Beckingsale; Robert Blake; Tong Chen 001; Guojing Cong; Carlos H. A. Costa; Johann Dahm; Giacomo Domeniconi; et al. (SC, 2019)

Video Action Recognition With an Additional End-to-End Trained Temporal Stream. - Guojing Cong; Giacomo Domeniconi; Joshua Shapiro; Chih-Chieh Yang; Barry Chen (WACV, 2019)

A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction. - Fan Zhou 010; Guojing Cong (CoRR, 2019)

Fast neural network training on a cluster of GPUs for action recognition with high accuracy. - Guojing Cong; Giacomo Domeniconi; Chih-Chieh Yang; Joshua Shapiro; Fan Zhou 010; Barry Chen (J. Parallel Distributed Comput., 2019)

Design of AI-Enhanced Drug Lead Optimization Workflow for HPC and Cloud. - Chih-Chieh Yang; Giacomo Domeniconi; Leili Zhang; Guojing Cong (IEEE BigData, 2020)

Partial data permutation for training deep neural networks. - Guojing Cong; Li Zhang; Chih-Chieh Yang (CCGRID, 2020)

Fast Training of Deep Neural Networks for Speech Recognition. - Guojing Cong; Brian Kingsbury; Chih-Chieh Yang; Tianyi Liu (ICASSP, 2020)

Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum. - Guojing Cong; Tianyi Liu (MLHPC/AI4S@SC, 2020)

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis. - Seung-Hwan Lim; Junghoon Chae; Guojing Cong; Drahomira Herrmannova; Robert M. Patton; Ramakrishnan Kannan; Thomas E. Potok (IEEE BigData, 2021)

Elastic distributed training with fast convergence and efficient resource utilization. - Guojing Cong (ICMLA, 2021)

Versatile feature learning with graph convolutions and graph structures. - Guojing Cong; Seung-Hwan Lim (ICDM (Workshops), 2021)

Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. - Yicong Zhu; Peng Zhang; Changnian Han; Guojing Cong; Yuefan Deng (ISC, 2021)

CASTELO: clustered atom subtypes aided lead optimization - a combined machine learning and molecular modeling method. - Leili Zhang; Giacomo Domeniconi; Chih-Chieh Yang; Seung-gu Kang; Ruhong Zhou; Guojing Cong (BMC Bioinform., 2021)

Artificial intelligence for accelerating time integrations in multiscale modeling. - Changnian Han; Peng Zhang 006; Danny Bluestein; Guojing Cong; Yuefan Deng (J. Comput. Phys., 2021)

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery. - Guojing Cong; Talia Ben-Naim; Victor Fung; Anshul Gupta; Rodrigo Neumann; Mathias Steiner (ICDM (Workshops), 2022)

Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning. - Guojing Cong; Seung-Hwan Lim; Steven Young (ICDM (Workshops), 2022)

Semi-Supervised Graph Structure Learning on Neuromorphic Computers. - Guojing Cong; Seung-Hwan Lim; Shruti R. Kulkarni; Prasanna Date; Thomas E. Potok; Shay Snyder; Maryam Parsa; Catherine D. Schuman (ICONS, 2022)

Exaflops Biomedical Knowledge Graph Analytics. - Ramakrishnan Kannan; Piyush Sao; Hao Lu 001; Jakub Kurzak; Gundolf Schenk; Yongmei Shi; Seung-Hwan Lim; Sharat Israni; Vijay Thakkar; Guojing Cong; Robert M. Patton; Sergio E. Baranzini; et al. (SC, 2022)

Neuromorphic Computing for Scientific Applications. - 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 (RSDHA@SC, 2022)

Prediction of CO2 Adsorption in Nano-Pores with Graph Neural Networks. - Guojing Cong; Anshul Gupta; Rodrigo Neumann; Maíra de Bayser; Mathias Steiner; Breanndán Ó Conchúir (CoRR, 2022)

Scalable multiscale modeling of platelets with 100 million particles. - Changnian Han; Peng Zhang; Yicong Zhu; Guojing Cong; James R. Kozloski; Chih-Chieh Yang; Leili Zhang; Yuefan Deng (J. Supercomput., 2022)

Clustering and GNN prediction with DrugMatrix. - Jiaji Ma 003; Guojing Cong; Scott Auerbach (IEEE Big Data, 2023)

Clustering High-dimensional Toxicogenomics Data with Rare Signals. - Guojing Cong; Scott Auerbach (ICDM (Workshops), 2023)

Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. - Guojing Cong; Shruti R. Kulkarni; Seung-Hwan Lim; Prasanna Date; Shay Snyder; Maryam Parsa; Dominic Kennedy; Catherine D. Schuman (ICMLA, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Optimizing Distributed Training on Frontier for Large Language Models. - Sajal Dash; Isaac Lyngaas; Junqi Yin; Xiao Wang 004; Romain Egele; Guojing Cong; Feiyi Wang; Prasanna Balaprakash (CoRR, 2023)

AI-aided multiscale modeling of physiologically-significant blood clots. - Yicong Zhu; Changnian Han; Peng Zhang; Guojing Cong; James R. Kozloski; Chih-Chieh Yang; Leili Zhang; Yuefan Deng (Comput. Phys. Commun., 2023)

Improving materials property predictions for graph neural networks with minimal feature engineering *. - Guojing Cong; Victor Fung (Mach. Learn. Sci. Technol., 2023)

Transductive Spiking Graph Neural Networks for Loihi. - Shay Snyder; Victoria Clerico; Guojing Cong; Shruti R. Kulkarni; Catherine D. Schuman; Sumedh R. Risbud; Maryam Parsa (ACM Great Lakes Symposium on VLSI, 2024)

Cross-tissue, Cross-platform Prediction and Validation of Toxicogenomics Profiles with Deep Learning and Clustering. - Trang Do; Richard Kim; Scott Auerbach; Warren M. Casey; Andrew A. Rooney; Guojing Cong (ICDM (Workshops), 2024)

Predicting Drug Effects from High-Dimensional, Asymmetric Drug Datasets by Using Graph Neural Networks: A Comprehensive Analysis of Multitarget Drug Effect Prediction. - Avishek Bose; Guojing Cong (ICMLA, 2024)

Exploration of Novel Neuromorphic Methodologies for Materials Applications. - Derek Gobin; Shay Snyder; Guojing Cong; Shruti R. Kulkarni; Catherine D. Schuman; Maryam Parsa (ICONS, 2024)

Comparative Study of Large Language Model Architectures on Frontier. - Junqi Yin; Avishek Bose; Guojing Cong; Isaac Lyngaas; Quentin Anthony (IPDPS, 2024)

Optimizing Distributed Training on Frontier for Large Language Models. - Sajal Dash; Isaac Lyngaas; Junqi Yin; Xiao Wang 004; Romain Egele; J. Austin Ellis; Matthias Maiterth; Guojing Cong; Feiyi Wang; Prasanna Balaprakash (ISC, 2024)

Completion of the DrugMatrix Toxicogenomics Database using 3-Dimensional Tensors. - Tan Nguyen; Guojing Cong (CoRR, 2025)