Published Papers

• W. Zheng, J. Kordas, T. J Skluzacek, R. Kettimuthu, I. Foster, Globus service enhancements for exascale applications and facilities, The International Journal of High Performance Computing Applications, September 2024. [pdf] [bibtex]

• W. Zheng, J. Park, P. Kenesei, A. Ali, Z. Liu, I. Foster, N. Schwarz, R. Kettimuthu, A. Miceli and H. Sharma, Rapid detection of rare events from in situ X-ray diffraction data using machine learning, JOURNAL OF APPLIED CRYSTALLOGRAPHY, July 2024. [pdf] [bibtex]

• K. Shaik, D. Wang, W. Zheng, Q. Cao, H. Fan, P. Schwartz, Y. Feng, S3LLM: Large-Scale Scientific Software Understanding with LLMs Using Source, Metadata, and Document, International Conference on Computational Science (ICCS) 2024. [pdf] [bibtex]

• S. Song, Y. Huang, P. Jiang, X. Yu, W. Zheng, S. Di, Q. Cao, Y. Feng, Z. Xie, F. Cappello, CereSZ: Enabling and Scaling Error-bounded Lossy Compression on Cerebras CS-2, Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing (HPDC’24), [pdf] [bibtex]

• J. Pruyne, V. Hayot-Sasson, W. Zheng, R. Chard, J. M Wozniak, T. Bicer, K. Chard, I. T Foster, Steering a Fleet: Adaptation for Large-Scale, Workflow-Based Experiments, arXiV, [pdf] [bibtex]

• Y. Feng, S. Vanam, M. Cherukupally, W. Zheng, M. Qiu, H. Chen, Investigating code generation performance of ChatGPT with crowdsourcing social data, 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC). [pdf] [bibtex]

• W. Zheng, D. Wang, F. Song, A Distributed-GPU Deep Reinforcement Learning System for Solving Large Graph Optimization Problems, ACM Transactions on Parallel Computing 2023. [pdf] [bibtex]

• Y. Feng, D. Zhong, P. Sun, W. Zheng, Q. Cao, X. Luo, Z. Lu, Micromobility in smart cities: A closer look at shared dockless e-scooters via big social data. IEEE International Conference on Communications, June 2021. [pdf] [bibtex]

• W. Zheng, D. Wang, F. Song, Designing a parallel Feel-the-Way clustering algorithm on HPC systems, The International Journal of High Performance Computing Applications, November 2020. [pdf] [bibtex]

• W. Zheng, D. Wang, F. Song, OpenGraphGym: A Parallel Reinforcement Learning Framework for Graph Optimization Problems, International Conference on Computational Science (ICCS) 2020. [pdf] [bibtex]

• W. Zheng, D. Wang, F. Song, FQL: An Extensible Feature Query Language and Toolkit on Searching Software Characteristics for HPC Applications in: Proceedings of the International Workshop on Software Engineering for HPC-Enabled Research, Supercomputing 2019 (SE-HER’19), Nov. 2019. [pdf] [bibtex]

• W. Zheng, D. Wang, F. Song, XScan: An Integrated Tool for Understanding Open Source Community-Based Scientific Code, International Conference on Computational Science (ICCS) 2019. [pdf] [bibtex]

• W. Zheng, F. Song, L. Lin, Z. Chen, Scaling Up Parallel Computation of Tiled QR Factorizations by a Distributed Scheduling Runtime System and Analytical Modeling, Parallel Processing Letter 28(01). [pdf] [bibtex]

• W. Zheng, F. Song, D. Wang, Design and Implementation of an Efficient Parallel Feel-the-Way Clustering Algorithm on High Performance Computing Systems, Purdue e-Pubs [pdf] [bibtex]

• D. Wang, F. Song, W. Zheng, Application Software Analytics Toolkit for Facilitating the Understanding, Componentization, and Refactoring of Large-Scale Scientific Models, 9th International Congress on Environmental Modelling and Software. [pdf] [bibtex]

• W. Zheng, F. Song, L. Lin, Designing a Synchronization-reducing Clustering Method on Manycores: Some Issues and Improvements, in: Proceedings of the Workshop on Machine Learning in High Performance Computing Environments, Supercomputing 2017 (MLHPC’17), Nov. 2017. [pdf] [bibtex]

• W. Zheng, F. Song, L. Lin, Z. Chen, suCAQR: A simplified communication-avoiding QR factorization solver using the TBLAS framework, in: Proceedings of the 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS’16), Dec. 2016. [pdf] [bibtex]

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