Hao Lu

According to our database, Hao Lu authored at least 22 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences.

Darren J. Hsu, Hao Lu, Aditya Kashi, Michael A. Matheson, John Gounley, Feiyi Wang, Wayne Joubert, Jens Glaser

Int. J. High Perform. Comput. Appl., November, 2023

Optimizing Communication in 2D Grid-Based MPI Applications at Exascale.

Hao Lu, Piyush Sao, Michael A. Matheson, Ramakrishnan Kannan, Feiyi Wang, Thomas E. Potok

Proceedings of the 30th European MPI Users' Group Meeting, 2023

2022

Climbing the Summit and Pushing the Frontier of Mixed Precision Benchmarks at Extreme Scale.

Hao Lu, Michael A. Matheson, Vladyslav Oles, J. Austin Ellis, Wayne Joubert, Feiyi Wang

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Exaflops Biomedical Knowledge Graph Analytics.

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

Proceedings of the SC22: International Conference for High Performance Computing, 2022

2021

Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters.

Piyush Sao, Hao Lu, Ramakrishnan Kannan, Vijay Thakkar, Richard W. Vuduc, Thomas E. Potok

Proceedings of the HPDC '21: The 30th International Symposium on High-Performance Parallel and Distributed Computing, 2021

Identification of Critical Infrastructure via PageRank.

Bill Kay, Hao Lu, Pravallika Devineni, Anika Tabassum, Supriya Chinthavali, Sangkeun Matt Lee

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Performance Evaluation of Python Based Data Analytics Frameworks in Summit: Early Experiences.

Benjamín Hernández, Suhas Somnath, Junqi Yin, Hao Lu, Joe Eaton, Peter Entschev, John Kirkham, Zahra Ronaghi

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Scalable knowledge graph analytics at 136 petaflop/s.

Ramakrishnan Kannan, Piyush Sao, Hao Lu, Drahomira Herrmannova, Vijay Thakkar, Robert M. Patton, Richard W. Vuduc, Thomas E. Potok

Proceedings of the International Conference for High Performance Computing, 2020

Toward Quantifying Vulnerabilities in Critical Infrastructure Systems.

Pravallika Devineni, Bill Kay, Hao Lu, Anika Tabassum, Supriya Chinthavali, Sangkeun Matt Lee

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2018

Efficient, Parallel At-scale Correlation Analysis for Atom Probe Tomography on Hybrid Architectures.

Hao Lu, Sudip K. Seal, Gregory Muzyn, Wei Guo, Jonathan D. Poplawsky

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Distributed Louvain Algorithm for Graph Community Detection.

Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Hao Lu, Daniel G. Chavarría-Miranda, Arif Khan, Assefaw Hadish Gebremedhin

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Scalable Proximity-Based Methods for Large-Scale Analysis of Atom Probe Data.

Hao Lu, Sudip K. Seal, Jonathan D. Poplawsky

Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

2017

Algorithms for Balanced Graph Colorings with Applications in Parallel Computing.

Hao Lu, Mahantesh Halappanavar, Daniel G. Chavarría-Miranda, Assefaw Hadish Gebremedhin, Ajay Panyala, Ananth Kalyanaraman

IEEE Trans. Parallel Distributed Syst., 2017

Spherical Region Queries on Multicore Architectures.

Hao Lu, Sudip K. Seal, Wei Guo, John Poplawsky

Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms, 2017

Scalable static and dynamic community detection using Grappolo.

Mahantesh Halappanavar, Hao Lu, Ananth Kalyanaraman, Antonino Tumeo

Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

Accelerating Graph Community Detection with Approximate Updates via an Energy-Efficient NoC.

Karthi Duraisamy, Hao Lu, Partha Pratim Pande, Ananth Kalyanaraman

Proceedings of the 54th Annual Design Automation Conference, 2017

2016

High-Performance and Energy-Efficient Network-on-Chip Architectures for Graph Analytics.

Karthi Duraisamy, Hao Lu, Partha Pratim Pande, Ananth Kalyanaraman

ACM Trans. Embed. Comput. Syst., 2016

Fast Uncovering of Graph Communities on a Chip: Toward Scalable Community Detection on Multicore and Manycore Platforms.

Ananth Kalyanaraman, Mahantesh Halappanavar, Daniel G. Chavarría-Miranda, Hao Lu, Karthi Duraisamy, Partha Pratim Pande

Found. Trends Electron. Des. Autom., 2016

2015

Parallel heuristics for scalable community detection.

Hao Lu, Mahantesh Halappanavar, Ananth Kalyanaraman

Parallel Comput., 2015

Balanced Coloring for Parallel Computing Applications.

Hao Lu, Mahantesh Halappanavar, Daniel G. Chavarría-Miranda, Assefaw Hadish Gebremedhin, Ananth Kalyanaraman

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

High performance and energy efficient wireless NoC-enabled multicore architectures for graph analytics.

Karthi Duraisamy, Hao Lu, Partha Pratim Pande, Ananth Kalyanaraman

Proceedings of the 2015 International Conference on Compilers, 2015

2014

Parallel Heuristics for Scalable Community Detection.

Hao Lu, Mahantesh Halappanavar, Ananth Kalyanaraman, Sutanay Choudhury

Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014