Guojing Cong

发表

Designing irregular parallel algorithms with mutual exclusion and lock-free protocols

David A. Bader, Guojing Cong, Guojing Cong, 2006, J. Parallel Distributed Comput..

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method pdf

Guojing Cong, Leili Zhang, Giacomo Domeniconi, 2020, BMC Bioinformatics.

SWARM: A Parallel Programming Framework for Multicore Processors

David A. Bader, Guojing Cong, 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

Design of Multithreaded Algorithms for Combinatorial Problems

David A. Bader, Guojing Cong, John Feo, 2007, Handbook of Parallel Computing.

An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications

Guojing Cong, Minwei Feng, Onkar Bhardwaj, 2017, 2017 46th International Conference on Parallel Processing (ICPP).

A Productivity Centered Tools Framework for Application Performance Tuning

Seetharami R. Seelam, Guojing Cong, I-Hsin Chung, 2007 .

An efficient approach for solving large stochastic unit commitment problems arising in a California ISO planning model

Guojing Cong, Deepak Rajan, Tiziano Parriani, 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

A study on the locality behavior of parallel and sequential algorithms for connectivity problems

Guojing Cong, Simone Sbaraglia, 2006 .

Hybrid Programming With SIMPLE

David A. Bader, Guojing Cong, Guojing Cong, 2011, Encyclopedia of Parallel Computing.

A scalable, asynchronous spanning tree algorithm on a cluster of SMPs

Guojing Cong, Hanhong Xue, Guojing Cong, 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

Fast Training of Deep Neural Networks for Speech Recognition

Brian Kingsbury, Guojing Cong, Chih-Chieh Yang, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Spanning Tree, Minimum Weight

David A. Bader, Guojing Cong, Guojing Cong, 2011, Encyclopedia of Parallel Computing.

Application tuning through bottleneck-driven refactoring

Guojing Cong, Hiroki Murata, I-Hsin Chung, 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW).

A Framework for Automated Per- formance Bottleneck Detection

Seetharami R. Seelam, Guojing Cong, I-Hsin Chung, 2008 .

Accelerating Deep Neural Network Training for Action Recognition on a Cluster of GPUs

Fan Zhou, Guojing Cong, Giacomo Domeniconi, 2018, 2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD).

Accelerating deep neural network learning for speech recognition on a cluster of GPUs

Brian Kingsbury, George Saon, Fan Zhou, 2017, MLHPC@SC.

Fast shared-memory algorithms for computing the minimum spanning forest of sparse graphs

David A. Bader, Guojing Cong, Guojing Cong, 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

Foreword to the special issue of the 18th IEEE international conference on computational science and engineering (CSE2015)

João M. P. Cardoso, Christian Plessl, Guojing Cong, 2017, Concurr. Comput. Pract. Exp..

On the convergence properties of a K-step averaging stochastic gradient descent algorithm for nonconvex optimization pdf

Fan Zhou, Guojing Cong, Guojing Cong, 2017, IJCAI.

Workload Performance Characterization of DARPA HPCS Benchmarks

Guojing Cong, Seetharami Seelam, I-Hsin Chung, 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction pdf

Fan Zhou, Guojing Cong, Guojing Cong, 2019, ArXiv.

Fast PGAS Implementation of Distributed Graph Algorithms

Guojing Cong, Vijay A. Saraswat, George Almási, 2010, 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis.

On the architectural requirements for efficient execution of graph algorithms

David A. Bader, Guojing Cong, John Feo, 2005, 2005 International Conference on Parallel Processing (ICPP'05).

Dynamics-Based Peptide-MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO.

Guojing Cong, Leili Zhang, Giacomo Domeniconi, 2020, Journal of chemical theory and computation.

An Efficient Framework for Multi-dimensional Tuning of High Performance Computing Applications

Guojing Cong, Hiroki Murata, I-Hsin Chung, 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium.

A productivity centered application performance tuning framework

Guojing Cong, Seetharami Seelam, I-Hsin Chung, 2007, VALUETOOLS.

Parallel Strategies for Solving Large Unit Commitment Problems in the California ISO Planning Model

Guojing Cong, Deepak Rajan, Carol Meyers, 2015, 2015 IEEE International Parallel and Distributed Processing Symposium.

On Adam Trained Models and a Parallel Method to Improve the Generalization Performance

Guojing Cong, Luca Buratti, Guojing Cong, 2018, 2018 IEEE/ACM Machine Learning in HPC Environments (MLHPC).

Reducing global reductions in large-scale distributed training

Guojing Cong, Chih-Chieh Yang, Fan Zhou, 2019, ICPP Workshops.

Locality behavior of parallel and sequential algorithms for irregular graph problems

Guojing Cong, Tong Wen, Guojing Cong, 2007 .

Efficient Parallel Graph Algorithms for Multicore and Multiprocessors

David A. Bader, Guojing Cong, Guojing Cong, 2007, Handbook of Parallel Computing.

A Productivity Centered Tools Framework for Application Performance Tuning

Guojing Cong, Seetharami Seelam, I-Hsin Chung, 2007, Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007).

Tool-assisted Optimization of Shared-memory Accesses in UPC Applications

Guojing Cong, Hiroki Murata, Hui-Fang Wen, 2012, 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems.

Composable Locality Optimizations for Accelerating Parallel Forest Computations

Guojing Cong, Ilie Gabriel Tanase, 2016, 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS).

Towards a framework for automated performance tuning

Guojing Cong, Seetharami Seelam, I-Hsin Chung, 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

Artificial intelligence for accelerating time integrations in multiscale modeling

Guojing Cong, Yuefan Deng, Danny Bluestein, 2020, J. Comput. Phys..

Optimizing Large-scale Graph Analysis on Multithreaded, Multicore Platforms

Guojing Cong, Konstantin Makarychev, Guojing Cong, 2011, 2012 IEEE 26th International Parallel and Distributed Processing Symposium.

The Euler tour technique and parallel rooted spanning tree

David A. Bader, Guojing Cong, Guojing Cong, 2004, International Conference on Parallel Processing, 2004. ICPP 2004..

Workload performance characterization of DARPA HPCS benchmarks

Guojing Cong, Seetharami Seelam, I-Hsin Chung, 2010, Concurr. Comput. Pract. Exp..

Improving Memory Access Locality for Large-Scale Graph Analysis Applications

Guojing Cong, Konstantin Makarychev, Guojing Cong, 2009, PDCCS.

Fast Parallel Connected Components Algorithms on GPUs

Guojing Cong, Paul Muzio, Guojing Cong, 2014, Euro-Par Workshops.

Practical Efficiency of Asynchronous Stochastic Gradient Descent

Guojing Cong, Onkar Bhardwaj, 2016, 2016 2nd Workshop on Machine Learning in HPC Environments (MLHPC).

Exploring Distributed Memory Parallel CPLEX

Guojing Cong, D Rajan, J Magerlein, 2014 .

Inefficiency of stochastic gradient descent with larger mini-batches (and more learners)

Guojing Cong, Onkar Bhardwaj, 2017 .

A framework for automated performance bottleneck detection

Guojing Cong, Seetharami Seelam, I-Hsin Chung, 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

A static analysis tool using a three-step approach for data races in HPC programs

Guojing Cong, Hiroki Murata, I-Hsin Chung, 2012, PADTAD 2012.

Mapping applications for high performance on multithreaded, NUMA systems

Guojing Cong, Hui-Fang Wen, Guojing Cong, 2013, CF '13.

Accelerating Data Loading in Deep Neural Network Training

Guojing Cong, Chih-Chieh Yang, Guojing Cong, 2019, 2019 IEEE 26th International Conference on High Performance Computing, Data, and Analytics (HiPC).

Fast neural network training on a cluster of GPUs for action recognition with high accuracy

Guojing Cong, Giacomo Domeniconi, Chih-Chieh Yang, 2019, J. Parallel Distributed Comput..

An experimental study of parallel biconnected components algorithms on symmetric multiprocessors (SMPs)

David A. Bader, Guojing Cong, Guojing Cong, 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

Solving Large, Irregular Graph Problems Using Adaptive Work-Stealing

Sriram Krishnamoorthy, Guojing Cong, Vijay A. Saraswat, 2008, 2008 37th International Conference on Parallel Processing.

Fast PGAS connected components algorithms

Guojing Cong, Vijay Saraswat, Gheorghe Almasi, 2009, PGAS '09.

A fast, parallel spanning tree algorithm for symmetric multiprocessors

David A. Bader, Guojing Cong, 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

A productivity centered application performance tuning framework

Seetharami R. Seelam, Guojing Cong, I-Hsin Chung, 2007, Valuetools 2007.

Graphics Processing Unit

Leonid Oliker, John Shalf, David Donofrio, 2011, Encyclopedia of Parallel Computing.

A fast, parallel spanning tree algorithm for symmetric multiprocessors

David A. Bader, Guojing Cong, Guojing Cong, 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

A Synchronous Parallel Max-Flow Algorithm for Real-World Networks

Guojing Cong, 2014, 2014 IEEE Intl Conf on High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC,CSS,ICESS).

A Hierarchical, Bulk-Synchronous Stochastic Gradient Descent Algorithm for Deep-Learning Applications on GPU Clusters

Guojing Cong, Onkar Bhardwaj, 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

Memory Centric Computation (Mc2) for Large-Scale Graph Processing

Guojing Cong, Kattamuri Ekanadham, Guojing Cong, 2015, 2015 27th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD).

Maximizing the performance of irregular applications on multithreaded, NUMA systems

Guojing Cong, Hui-Fang Wen, Guojing Cong, 2013, IA3 '13.

Guided Performance Analysis Combining Profile and Trace Tools

Bernd Mohr, Jesús Labarta, Guojing Cong, 2010, Euro-Par Workshops.

Fast Shared-Memory Algorithms for Computing the Minimum Spanning Forest of Sparse Graphs

David A. Bader, Guojing Cong, 2004, IPDPS.

An Empirical Analysis of Parallel Random Permutation Algorithms ON SMPs

David A. Bader, Guojing Cong, Guojing Cong, 2006, PDCS.

Accelerating Minimum Spanning Forest Computations on Multicore Platforms

Yinglong Xia, Guojing Cong, Ilie Gabriel Tanase, 2015, Euro-Par Workshops.

Preparation and optimization of a diverse workload for a large-scale heterogeneous system

Bronis R. de Supinski, John A. Gunnels, Yoonho Park, 2019, SC.