Chunhua Liao


Portrait of  Chunhua Liao
  • Title
    Senior Computer Scientist
  • Email
  • Phone
    (925) 422-8190
  • Organization
    Not Available

Dr. Chunhua "Leo" Liao is a senior computer scientist in the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory. His research focus has been on software techniques to improve the performance and correctness of parallel programs. His research interests encompass parallel languages, especially OpenMP, optimizing compilers, runtime systems, and programming tools. 

Dr. Liao received his Ph.D. degree in Computer Science from University of Houston in Aug. 2007. He also holds M.E. and B.E. degrees in Computer Science from Sichuan University in China.

Research Experience

Dr. Liao has been the co-principal investigator, a critical contributor, and a leading maintainer of the widely used ROSE compiler infrastructure since 2007. He is the leading author for an OpenMP implementation (XOMP) supporting multiple runtime libraries, effective source-to-source outlining, semantic-aware automatic parallelization, OpenMP accelerator support (HOMP), and DataRaceBench. He is also a critical contributor to compiler-based resilience, autotuning, runtime error checking, and so on. In 2009, the ROSE team was a recipient of the prestigious R&D 100 Award due to their significant contributions in making compiler technologies more accessible. 

Dr. Liao has been one of proposal initiators, principal investigators and senior personnel for many collaborative research projects, including:

  • HPC-FAIR: A Framework Managing Data and AI Models for Analyzing and Optimizing Scientific Applications (9/20-8/23)
  • RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence (10/20-9/25),
  • Achieving Peak Performance of HPC Applications By Optimizing Parallelism (10/20-9/23),
  • XPlacer: Extensible and Portable Optimizations of Data Placement in Memory (10/17-9/20),
  • RAPIDS, SciDAC Institute for Computer Science and Data (10/17-9/20),
  • Data Race Free HPC Software (10/16-9/19),  
  • Exascale Code Generation Toolkit (10/16-3/19),
  • Institute for Sustained Performance, Energy, and Resilience (SUPER) (10/11-09/16),
  • DSL Technology for Exascale Computing (D-TEC) (09/12-08/15),
  • FAIL-SAFE: Fault Aware Intelligent Software For Exascale (12/13-07/15),
  • A Node-Level Programming Model Framework for Exascale(04/12-03/15),
  • Compiled MPI: Cost-Effective Exascale Application Development (10/10-09/13),
  • Thrifty: An Exascale Architecture for Energy Proportional Computing (10/10-09/13), 
  • CoDEx: A Hardware/Software Codesign Environment for the Exascale Era (10/10-09/13), 
  • Semantics-Driven Optimization of Scientific Applications (10/09-09/12)

Prior to LLNL, he was a key developer for an OpenMP reference compiler named OpenUH, an academic branch of the Open64 compiler. He was also a contributor to the Dragon Analysis Tool and OpenMP validation suite.

Selected Software Releases

  • Ethan Dorta, Chunhua Liao, Yonghong Yan, Generating and Analyzing Program Call Graphs using Ontology, Workshop on Programming and Performance Visualization Tools, held in conjunction with SC'22, LLNL-CONF-838827
  • Winson Chen, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao, Murali Emani, Early Experience with Transformer-Based Similarity Analysis for DataRaceBench, the Sixth International Workshop on Software Correctness for HPC Applications (Correctness 2022), LLNL-CONF-838838
  • Zifan Nan, Mithil Dave, Xipeng Shen, Chunhua Liao, Tristan Vanderbruggen, Pei-Hung Lin, Murali Emani, Interactive NLU-Powered Ontology-Based Workflow Synthesis for FAIR Support of HPC, the 2022 IEEE/ACM 9th International Workshop on HPC User Support Tools (HUST-22) held in conjunction with SC '22, LLNL-CONF-833524
  • Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani and Hailu Xu, Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study, 1st Workshop on Trustable and Ethical Machine Learning, During Transdisciplinary AI, Laguna Hills, CA, USA, 19-21 September 2022, LLNL-CONF-832022
  • José Wesley de Souza Magalhães, Chunhua Liao , Fernando Magno Quintão Pereira, Automatic Inspection of Program State in an Uncooperative Environment, Software: Practice and Experience, 2022, LLNL-JRNL-826460
  • Hailu Xu, Pei-Hung Lin, Murali Emani, Liting Hu, Chunhua Liao, X-Unified: A Framework for Guiding Optimal Use of GPU Unified Memory, IEEE Access, 2022, LLNL-CONF-798297
  • Patrick Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani and Xipeng Shen, Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines, 2nd International Workshop on Software Architecture and Machine Learning, 2022, , LLNL-CONF-837414
  • Giorgis Georgakoudis, Thomas Scogland, Chunhua Liao and Bronis de Supinski, Extending OpenMP to Support Automated Function Specialization Across Translation Units, IWOMP 2022, Chattanooga, TN, Sept. 27-30, 2022, LLNL-CONF-837685
  • Yaying Shi, Anjia Wang, Yonghong Yan, Chunhua Liao, RDS: A Cloud-Based Metaservice for Detecting Data Races in Parallel Programs, 14th IEEE/ACM International Conference on Utility and Cloud Computing, University of Leicester, Leicester, UK, December 6-9, 2021 LLNL-CONF-809187
  • Pei-Hung Lin, Chunhua Liao. High-Precision Evaluation of Both Static and Dynamic Tools using DataRaceBench. International Workshop on Software Correctness for HPC Applications (Correctness), St. Louis, MO, Nov. 2021, LLNL-CONF-825647
  • Gaurav Verma, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Barbara Chapman, HPCFAIR: Enabling FAIR AI for HPC Applications, 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), LLNL-CONF-826435
  • Chunhua Liao, Anjia Wang, Giorgis Georgakoudis, Bronis R. de Supinski,Yonghong Yan, David Beckingsale, and Todd Gamblin, Extending OpenMP for Machine Learning-Driven Adaptation, Eighth Workshop on Accelerator Programming Using Directives (WACCPD), Nov. 2021, LLNL-CONF-826432 
  • Chunhua Liao, Pei-Hung Lin, Gaurav Verma, Tristan Vanderbruggen, Murali Emani, Zifan Nan, Xipeng Shen, HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing, 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), LLNL-CONF-826494
  • Xinyao Yi, David Stokes, Yonghong Yan, Chunhua Liao, CUDAMicroBench: Microbenchmarks to Assist CUDA Performance Programming, 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 17-21 June 2021 , Portland, OR, USA , LLNL-CONF-819919
  • Zifan Nan, Hui Guan, Xipeng Shen, and Chunhua Liao. Deep NLP-based co-evolvement for synthesizing code analysis from natural language. In Proceedings of the 30th ACM SIGPLAN International Conference on Compiler Construction, pp. 141-152. 2021. LLNL-CONF-794949
  • Justin Gosselin, Anjia Wang, Peter Pirkelbauer, Chunhua Liao, Yonghong Yan, and Damian Dechev, Extending as an Online Self-Learning Platform for Compiler Development, EduHPC, SC20 workshops
  • Gaurav Verma, Yaying Shi, Chunhua Liao, Barbara Chapman, and Yonghong Yan, Enhancing DataRaceBench for Evaluating DataRace Detection Tools, Correctness SC20 workshops
  • Gleison Mendonca, Chunhua Liao and Fernando Duarte, AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers, International Conference on Supercomputing, June 29-July 2 2020, Barcelona, Spain, LLNL-CONF-795158
  • Peter Pirkelbauer, Pei-Hung Li, Tristan Vanderbruggen , Chunhua Liao, XPlacer: Automatic Analysis of CPU/GPU Access Patterns, IPDPS 2020, LLNL-CONF-795057
  • Anjia Wang, Alok Mishra, Chunhua Liao, Yonghong Yan, and Barbara Chapman, Training for OpenMP Compiler Development from Cloud, Volume 11, Issue 1, pp. 53 - 60, Journal of Computational Science Education, Jan. 2020
  • Hailu Xu, Murali Emani, Pei-Hung Lin, Liting Hu, Chunhua Liao, Machine Learning Guided Optimal Use of GPU Unified Memory, MCHPC '19: Workshop on Memory Centric High Performance Computing. (LLNL-CONF-793704)
  • Anjia Wang, Alok Mishra, Chunhua Liao, Yonghong Yan, Barbara Chapman, Training for OpenMP Compiler Development from Cloud, Sixth SC Workshop on Best Practices for HPC Training and Education: BPHTE19, 2019 LLNL-CONF-791339
  • Alok Mishra, Anjia Wang, Chunhua Liao, Yonghong Yan, Barbara Chapman, FreeCompilerCamp: Online Training for Extending Compilers, SC'19 Research Poster submission, accepted (also selected as a Best Poster nominee).
  • Pei-Hung Lin, Chunhua Liao, Markus Schordan, Ian Karlin, Exploring Regression of Data Race Detection Tools Using DataRaceBench, Third International Workshop on Software Correctness for HPC Applications (Correctness 2019)
  • Anjia Wang, Yaying Shi, Xinyao Yi, Yonghong Yan, Chunhua Liao and Bronis R. de Supinski, "ompparser: A Standalone and Unified OpenMP Parser," Fifteenth International Workshop on OpenMP (IWOMP 2019), Auckland, New Zealand, September 11–13, 2019. (LLNL-CONF-774801).
  • Yonghong Yan, Anjia Wang, Chunhua Liao, Tom Scogland and Bronis R. de Supinski, Extending OpenMP Metadirective Semantics for Runtime Adaptation, Fifteenth International Workshop on OpenMP (IWOMP 2019), Auckland, New Zealand, September 11–13, 2019. (LLNL-CONF-774899)
  • Jie Ren, Chunhua Liao and Dong Li, Opera: Data Access Pattern Similarity Analysis To Optimize OpenMP Task Affinity, 24th International Workshop On High-level Parallel Programming Models And Supportive Environments (HIPS), Held in Conjunction With 33rd IPDPS International Parallel & Distributed Processing Symposium, May 20-24, 2019, Rio De Janeiro, Brazil
  • Pei-Hung Lin, Chunhua Liao, Markus Schordan, Ian Karlin: Runtime and Memory Evaluation of Data Race Detection Tools. In International Symposium on Leveraging Applications of Formal Methods, pp. 179-196. Springer, Cham, 2018.
  • Larisa Stoltzfus, Murali Emani, Pei-Hung Lin, and Chunhua Liao. Data Placement Optimization in GPU Memory Hierarchy using Predictive Modeling. In Proceedings of the Workshop on Memory Centric High Performance Computing (MCHPC'18). ACM, New York, NY, USA, 45-49.
  • M.Bari, L. Stoltzfus, P. Lin, C. Liao, M. Emani, B.Chapman, Is Data Placement Optimization Still Relevant on Newer GPUs? The 9th International Workshop on Performance Modeling, Benchmarking, and Simulation of High-Performance Computer Systems (PMBS18), Dallas, TX, Nov 12th, 2018
  • Chunhua Liao, Pei-Hung Lin, Markus Schordan and Ian Karlin, A Semantics-Driven Approach to Improving DataRaceBench's OpenMP Standard Coverage, IWOMP 2018: 14th International Workshop on OpenMP, Barcelona, Spain, September 26-28, 2018, Proceedings. 189-202. Springer Link, LLNL copyslides
  • Chunhua Liao, Pei-Hung Lin, Joshua Asplund, Markus Schordan and Ian Karlin, DataRaceBench: A Benchmark Suite for Systematic Evaluation of Data Race Detection Tools, The International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, Nov. 12-17, 2017 (Best Paper Nominee). LLNL copy, slides
  • A Proposal to OpenMP for Addressing the CPU Oversubscription Challenge, Yonghong Yan, Jeff R. Hammond, Chunhua Liao, and Alexandre E. Eichenberger, IWOMP 2016, Oct 6-7, 2016 Nara, Japan Springer Link
  • Pei-Hung Lin, Qing Yi, Daniel Quinlan, Chunhua Liao and Yongqing Yan, Automatically Optimizing Stencil Computations on Many-core NUMA Architectures, The 29th International Workshop on Languages and Compilers for Parallel Computing (LCPC 2016) September 28-30, 2016 Rochester NY, USA pdf
  • Yue Zhao, Guoyang Chen, Chunhua Liao and Xipeng Shen, Towards Ontology-Based Program Analysis, The European Conference on Object-Oriented Programming (ECOOP), July 17-22, 2016 Rome, Italy. pdf slides poster
  • Chunhua Liao, Pei-Hung Lin, Daniel J. Quinlan, Yue Zhao, and Xipeng Shen. 2015. Enhancing domain specific language implementations through ontology. In Proceedings of the 5th International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC '15). ACM, New York, NY, USA ACM Link slides
  • Pei-Hung Lin, Chunhua Liao, Daniel Quinlan and Stephen Guzik, Experiences of Using the OpenMP Accelerator Model to Port DOE Stencil Applications, 11th International Workshop on OpenMP, Oct 1-2, 2015, Aachen, Germany pdf slides
  • Yonghong Yan, Pei-Hung Lin, Chunhua Liao, Bronis R. de Supinski, and Daniel J. Quinlan. 2015. Supporting multiple accelerators in high-level programming models. In Proceedings of the Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), Pavan Balaji, Minyi Guo, and Zhiyi Huang (Eds.). ACM, New York, NY, USA, 170-180. ACM link
  • Jacob Lidman, Sally McKee, Daniel Quinlan and Chunhua Liao , An Automated Performance-Aware Approach to Reliability Transformations, Euro-Par 2014, 25-29 August, Porto, Portugal pdf
  • Hongyi Ma, Steve R. Diersen, Liqiang Wang, Chunhua Liao, Daniel Quinlan, and Zijiang Yang. 2013. Symbolic Analysis of Concurrency Errors in OpenMP Programs. In Proceedings of the 2013 42nd International Conference on Parallel Processing (ICPP '13). IEEE Computer Society, Washington, DC, USA, 510-516. IEEE Link
  • Chunhua Liao, Yonghong Yan, Bronis R. de Supinski, Daniel J. Quinlan and Barbara Chapman, Early Experiences With The OpenMP Accelerator Model, 9th International Workshop on OpenMP (IWOMP), Canberra, Australia, Sept. 16-18,2013  pdf slides
  • Jacob Lidman, Daniel J. Quinlan, Chunhua Liao and Sally A. McKee, ROSE::FTTransform::A Source-to-Source Translation Framework for Exascale Fault-Tolerance Research, Fault-Tolerance for HPC at Extreme Scale (FTXS 2012), Boston, June 25-28, 2012. slides
  • Sara Royuela, Alejandro Duran, Chunhua Liao and Daniel J. Quinlan, Auto-scoping for OpenMP tasks, The 8th International Workshop on OpenMP (IWOMP 2012), Rome, June 11-13, 2012.
  • Peter Pirkelbauer, Chunhua Liao, Thomas Panas and Dan Quinlan, Runtime Detection of C-Style Errors in UPC Code, Fifth Partitioned Global Address Space Conference (PGAS), Galveston, TX, Oct. 2011 pdf
  • Ananta Tiwari, Jeffrey K Hollingsworth, Chun Chen, Mary Hall, Chunhua Liao, Daniel J Quinlan, and Jacqueline Chame. Auto-tuning full applications: A case study. International Journal of High Performance Computing Applications,  Volume 25, Issue 3 (August 2011), Pages 286-294.
  • Chunhua Liao, Daniel J. Quinlan , Thomas Panas and Bronis de Supinski, A ROSE-based OpenMP 3.0 Research Compiler Supporting Multiple Runtime Libraries, international Workshop on OpenMP (IWOMP) 2010, accepted in March. 2010 LLNL-CONF-422873 pdf
  • Chunhua Liao, Daniel J. Quinlan, Jeremiah J. Willcock and Thomas Panas, Semantic-Aware Automatic Parallelization of Modern Applications Using High-Level Abstractions, Journal of Parallel Programming, Accepted in Jan. 2010 pdf
  • Chunhua Liao, Daniel J. Quinlan and Thomas Panas, Towards an Abstraction-Friendly Programming Model for High Productivity and High Performance Computing, Workshop on Non-Traditional Programming Models for High-Performance Computing, Los Alamos Computer Science Symposium (LACSS) 2009, Santa Fe, New Mexico, October 13-14, 2009 LLNL-CONF-417691 pdf .
  • Chunhua Liao, Daniel J. Quinlan, Richard Vuduc and Thomas Panas, Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization, The 22nd International Workshop on Languages and Compilers for Parallel Computing, Newark, Delaware, USA. October 8-10, 2009. pdf .
  • Chunhua Liao, Daniel J. Quinlan, Jeremiah J. Willcock and Thomas Panas, "Extending Automatic Parallelization to Optimize High-Level Abstractions for Multicore," In Proceedings of the 5th international Workshop on OpenMP: Evolving OpenMP in An Age of Extreme Parallelism (Dresden, Germany, June 03 - 05, 2009). pdf .
  • Chunhua Liao, A Compile-Time OpenMP Cost Model, Ph.D. dissertation, University of Houston, Texas, 2007.
  • Chunhua Liao, Oscar Hernandez, Barbara Chapman, Wenguang Chen and Weimin Zheng, OpenUH: An Optimizing, Portable OpenMP Compiler, Concurrency and Computation: Practice and Experience, Special Issue: Current Trends in Compilers for Parallel Computers, Vol. 19, no. 18, p 2317 - 2332, April. 2007.
  • Lei Huang, Barbara Chapman, Chunhua Liao, An Implementation and Evaluation of Thread Subteam for OpenMP Extensions, PMUP'06 (Programming Models for Ubiquitous Parallelism) workshop, Seattle, Washington, Sept. 16, 2006.
  • Chunhua Liao, Zhenying Liu, Lei Huang and Barbara Chapman, Evaluating OpenMP on Chip MultiThreading Platforms. First International Workshop on OpenMP (IWOMP). Eugene, Oregon USA. June 1-4, 2005.
  • Oscar Hernandez, Chunhua Liao and Barbara Chapman, A Tool to Display Array Access Patterns in OpenMP Programs, PARA'04 workshop on state-of-the-art in scientific computing, Lyngby, Copenhagen, Denmark, June 20-23, 2004.
  • Oscar Hernandez, Chunhua Liao and Barbara Chapman, Dragon: A static and dynamic tool for OpenMP, Workshop on OpenMP Applications and Tools (WOMPAT) 2004, pp.53-66, 2004.
  • 2018 DDS&T Excellence in Publication Award for the publication "DataRaceBench: A Benchmark Suite for Systematic Evaluation of Data Race Detection Tools", Lawrence Livermore National Laboratory
  • Outstanding Mentor, Lawrence Livermore National Laboratory, 2017
  • R&D 100 Award for the ROSE compiler, 2009
  • Computation Directorate Noteworthy Achievement Award, Lawrence Livermore National Laboratory, 2009
  • Computer Science Department Scholarship, University of Houston, 2006 - 2007
  • Computer Science Department Scholarship, University of Houston, 2005 - 2006
  • Shell Scholarship, University of Houston, 2004 – 2005