Seyong Lee
Senior Computer Scientist (Senior R&D Staff) in Future Technologies Group, Oak Ridge National Laboratory
CV :
Address : 		PDF
5100, MS 6173
P. O. Box 2008
Oak Ridge, TN 37831-9984
E-Mail Address:
lees2 AT ornl DOT gov
ORCID iD:
https://orcid.org/0000-0001-8872-4932

Research Interest

  • Programming Systems for Heterogeneous Computing
  • Program Analysis and Optimizing Compiler for High-Performance Computing
  • Compile-time/Runtime Performance Optimization on Emerging Hardware Architectures Including Multi-cores and Accelerators
  • Performance Portability
  • Performance Modeling

    • Education

  • Ph.D., School of ECE, Purdue University, West Lafayette, IN (May 2011)
             Advisor: Professor Rudolf Eigenmann
  • M.S., School of ECE, Purdue University, West Lafayette, IN (May 2004)
             Advisor: Professor Rudolf Eigenmann
  • B.S., School of Electrical Engineering, Seoul National University, South Korea (Feb. 1999)
             Advisor: Professor Beom Hee Lee

    • Research Projects

  • Brisbane: Productive Programming Systems in the Era of Extremely Heterogeneous and Ephemeral Computer Architectures, DoD, Advanced Computing Initiative (ACI)
  • Cosmic Castle: DARPA Domain Specific Systems on a Chip
  • RAPIDS: SciDAC Institute for Computer Science and Data
  • PROTEAS: PROgramming Toolchain for Emerging Architectures and Systems
  • CLACC: OpenACC Support in Clang and LLVM
  • OpenARC: Open Accelerator Research Compiler
  • Aspen: Abstract Scalable Performance Engineering Notation
  • ARES: Abstract Representations for the Extreme-Scale Stack
  • Vancouver: Productivity software for scalable heterogeneous computing
  • Oxbow: Application Characterization and Performance Analytics for Exascale Co-Design
  • OpenMP to GPU: Automatic translation and adaptation of OpenMP-based shared-memory programs onto GPUs
    1. Developed the compiler framework that translates OpenMP-based shared-memory programs into CUDA-based GPGPU programs and optimizes their performance automatically.
    2. Created a reference tuning framework, which is able to suggest applicable tuning configurations for a given input OpenMP program, generate CUDA code variants for each tuning configuration, and search the best optimizations for the generated CUDA program automatically.
  • ATune: Compiler-Driven Adaptive Execution
    1. Created a tuning system, which adaptively optimizes MPI applications in a distributed system.
    2. This project is parts of a larger effort that aims at creating a global information sharing system, where resources, such as software applications, computer platforms, and information can be shared, discovered, adapted to local needs.
  • iShare: Internet-sharing middleware and collaboration
    1. Developed domain-specific ranking and content search mechanisms for P2P-based Grid environment.
    2. Developed resource-availability-prediction mechanism for fine-grained cycle sharing system.
  • MaRCO: MapReduce with Communication Overlap
    1. Developed efficient communication overlapping mechanisms to increase the performance of Google's MapReduce system.

    Professional Service

  • Member of the OpenACC Technical Committee and Test-Suite Committee (OpenACC-standard.org)
  • Member of OpenMP Language Committee and OpenMP Accelerator Subcommittee
  • Member of SEED Review Committee, Computer Science and Mathematics Division, Oak Ridge National Laboratory
  • Member of Science Council, Computer Science and Mathematics Division, Oak Ridge National Laboratory, 6/2017 ~ 5/2020
  • Member of the NVIDIA PathForward Working Group, Exascale Computing Project PathForward Program, 2018 ~ 2020
  • Award Committee Member for 2017 IEEE CS TCHPC Award for Excellence for Early Career Researchers in High Performance Computing, 2017
  • Award Committee Member for 2018 Computer Science and Mathematics Division Awards, 2018 and 2019
  • Science and Innovation Culture Metric Committee, Computing and Computational Science Directorate, Oak Ridge National Laboratory, 2016
  • Guest Editor
  • the Special Issue on "High Performance Reconfigurable Computing" in Journal of Algorithms
  • the Special Issue on "Program Analysis and Optimizing Compilers for High-Performance Computing" in Journal of Electronics
    •
  • Program Committee Member : TPDS (2021), SC (2018, 2021), ASPLOS (2018), IPDPS(2017, 2018, 2019, and 2021), PPoPP (2014 and 2020), PACT (2019 and 2020), ISC (2019 and 2020), ICPP (2013, 2020, and 2021), HiPC (2019), Euro-Par (2017 and 2019), ICPADS(2013, 2014, 2015, 2016, and 2017), CCGrid (2015, 2016, and 2017), ADVCOMP (2017 and 2018), CANDAR (2016), PLC (2015), WRAp (2015, 2017, and 2018), WACCPD (2014, 2015, 2016, 2017, 2018, and 2019), AsHES (2016, 2017, 2018, 2019, 2020, and 2021), LHAM (2016, 2017, 2018, and 2020), CSA (2019), ISPA (2017 and 2018), IPCCC (2018, 2019, and 2020), HIPS (2019, 2020, 2021), REFAC (2019), LCPC (2019), CSE (2020)
  • External Reviewer (Journals, Conferences, Workshops, and research proposals)
  • Journals: TPDS (2014, 2016, 2018, and 2020), IEEE Micro (2017 and 2021), JPDC (2009, 2020, 2021), IJHPCA (2012, 2015, 2016, 2018, and 2020), IJPP (2018), ToMPECS (2015), ParCo (2013, 2015, 2017, 2018, and 2020), CyS (2015), ACMTACO (2013 and 2014), SOSYM (2011), SPE (2010, 2019, 2021), TWMS (2017), JES (2017), IJHPCN (2017), Computers (2017), TC (2017), FGCS (2018), OpenCS (2018), SoftwareX (2018 and 2019), VLSI (2018), Scientific Programming (2019), IEEE Access (2019), Algorithms (2020), TECS (2020), Mathematics (2020), Symmetry (2020)
  • Conferences: PACT (2010 and 2012), PLDI (2011), IPDPS (2010 and 2013), ICS (2008, 2011, 2013, and 2016), SC (2007 and 2013), CGO (2013 and 2014), HiPC (2009 and 2010), ICDCS (2006), ICPE (2011), GPC (2007 and 2008), INPAR (2012), ICPP (2019)
  • Workshops: LCPC (2006, 2007, 2011, and 2014), IWOMP (2007, 2009, and 2011), APPT (2011), PCGrid (2008), EPHAM (2008 and 2009)
  • Research Proposals: The General Research Fund, the Research Grants Council of Hong Kong (2011), Department of Energy (DOE) Office of Science Small Business Innovation Research (SBIR) & Small Business Technology Transfer (STTR) program (2015), Natural Sciences and Engineering Research Council of Canada (NSERC) (2019), Advancing Academic Research through Innovation in eScience and Data Science Technologies (eTEC) (2020), ETEC Proposal Review, the Netherlands e-Science Center (NLeSC) and The Dutch Research Council (NWO) (2020)

    • Recent Publications (Full Publication List)

    Anthony M. Cabrera, Aaron R. Young, Jacob Lambert, Zhili Xiao, Amy An, Seyong Lee, Zheming Jin, Jungwon Kim, Jeremy Buhler, Roger D. Chamberlain, and Jeffrey S. Vetter Towards Evaluating High-Level Synthesis Portability and Performance Between Intel and Xilinx FPGAs. 9th International Workshop on OpenCL and SYCL (IWOCL), 2021.

    Gregory Herschlag, Seyong Lee, Jeffrey S. Vetter, and Amanda Randles Analysis of GPU Data Access Patterns on Complex Geometries for the D3Q19 Lattice Boltzmann Algorithm. Transactions on Parallel and Distributed Systems (TPDS), 2021.

    Camille Coti, Joel E. Denny, Kevin Huck, Seyong Lee, Allen D. Malony, Sameer Shende, and Jeffrey S. Vetter OpenACC Profiling Support for Clang and LLVM using Clacc and TAU. Workshop on Programming and Performance Visualization Tools (ProTools 20), in conjunction with SC20, 2020.

    Mohammad Alaul Haque Monil, Seyong Lee, Jeffrey S. Vetter, and Allen D. Malony Understanding the Impact of Memory Access Patterns in Intel Processors. MCHPC20: Workshop on Memory Centric High Performance Computing, in conjunction with SC20, 2020.

    Mohammad Alaul Haque Monil, Mehmet E. Belviranli, Seyong Lee, Jeffrey S. Vetter, and Allen D. Malony Modeling Energy-Performance in Heterogeneous SOCs and Their Trade-Offs. The International Conference on Parallel Architectures and Compilation Techniques (PACT), 2020.

    Jacob Lambert, Seyong Lee, Jeffrey S. Vetter, and Allen D. Malony CCAMP: An Integrated Translation and Optimization Framework for OpenACC and OpenMP. SC 2020: The International Conference for High Performance Computing, Networking, Storage, and Analysis, 2020.

    Ryuta Tsunashima, Ryohei Kobayashi, Norihisa Fujita, Taisuke Boku, Seyong Lee, Jeffrey Vetter, Hitoshi Murai, Masahiro Nakao and Mitsuhisa Sato OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration. 13th International Symposium on High-level Parallel Programming and Applications (HLPP), Porto, Portugal, July, 2020.

    Jacob Lambert, Seyong Lee, Jeffrey S. Vetter, and Allen D. Malony In-Depth Optimization with the OpenACC-to-FPGA Framework on an Arria 10 FPGA. The Nineth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), in conjunction with IPDPS20, New Orleans, LA, USA, 2020.

    Roberto Gioiosa, Burcu O. Mutlu, Seyong Lee, Jeffrey S. Vetter, Giulio Picierro, and Marco Cesati. The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems. Proceedings of the 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit (GPGPU'20), in conjunction with PPoPP20, San Diego, CA, USA, 2020

    Blaise Tine, Fares Elsabbagh, Seyong Lee, Jeffrey Vetter, and Hyesoon Kim. Cash: A Single-Source Hardware-Software Codesign Framework for Rapid Prototyping. 28th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2020), Poster, Seaside, California, USA, 2020.

    Blaise Tine, Seyong Lee, Jeffrey Vetter, and Hyesoon Kim. Productive Hardware Designs using Hybrid HLS-RTL Development. 28th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2020), Poster, Seaside, California, USA, 2020.

    Ryuta Tsunashima, Ryohei Kobayashi, Norihisa Fujita, Ayumi Nakamichi, Taisuke Boku, Seyong Lee, Jeffrey Vetter, Hitoshi Murai, and Mitsuhisa Sato. Enabling OpenACC Programming on Multi-hybrid Accelerated with GPU and FPGA. International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2020), Poster, Fukuoka, Japan, 2020.

    Forrest Shriver, Seyong Lee, Steven Hamilton, Justin Watson, and Jeffrey Vetter. Enhancing Monte Carlo proxy applications on GPUs , 10th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS19), in conjunction with SC19,, Denver, Colorado, USA, 2019.

    Forrest Shriver, Seyong Lee, Steven Hamilton, Jeffrey Vetter, and Justin Watson. VEXS, An Open Platform for the Study of Continuous-Energy Neutron Transport Cross-Section Lookup Algorithms on GPUs, MC19: International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, Portland, Oregon, USA, 2019.

    David Ojika, Ann Gordon-Ross, Herman Lam, Shinjae Yoo, Younggang Cui, Zhihua Dong, Kirstin Kleese Van Dam, Seyong Lee, and Thorsten Kurth. PCS: A Productive Computational Science Platform, International Workshop on Exploitation of High Performance Heterogeneous Architectures and Accelerators (WEHA), in conjunction with HPCS19, Dublin, Ireland, 2019.

    Jacob Lambert, Seyong Lee, Allen D. Malony, and Jeffrey S. Vetter. CCAMP: OpenMP and OpenACC Interoperable Framework , Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar), in conjunction with Euro-Par19, Gõttingen, Germany, 2019.

    Seyong Lee, John Gounley, Amanda Randles, and Jeffrey S. Vetter. Performance Portability Study for Massively Parallel Computational Fluid Dynamics Application on Scalable Heterogeneous Architectures, Journal of Parallel and Distributed Computing (JPDC), 2019.

    Joel E. Denny, Seyong Lee, and Jeffrey S. Vetter. Clacc: Translating OpenACC to OpenMP in Clang, IEEE/ACM 5th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), in conjunction with SC18, Dallas, Texas, USA, 2018

    Mehmet E. Belviranli, Seyong Lee, and Jeffrey S. Vetter. Programming the EMU Architecture: Algorithm Design Considerations for Migratory-threads-based Systems , SC18: ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Poster, Dallas, Texas, USA, 2018.

    Seyong Lee, Jacob Lambert, Jungwon Kim, Jeffrey S. Vetter, and Allen D. Malony. OpenACC to FPGA: A Directive-Based High-Level Programming Framework for High-Performance Reconfigurable Computing, SC18: ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Poster, Dallas, Texas, USA, 2018.

    Pak Markthub, Mehmet E. Belviranli, Seyong Lee, Jeffrey S. Vetter, and Satoshi Matsuoka. DRAGON: Breaking GPU Memory Capacity Limits with Direct NVM Access, SC18: ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, Texas, USA, 2018.

    Michael Wolfe, Seyong Lee, Jungwon Kim, Xiaonan Tian, Rengan Xu, Barbara Chapman, Sunita Chandrasekaran. The OpenACC data model: Preliminary study on its major challenges and implementations, Parallel Computing: systems & applications, Volume 27, Pages 15-27, 2018.

    Mehmet E. Belviranli, Seyong Lee, and Jeffrey S. Vetter. Designing Algorithms for the EMU Migrating-threads-based Algorithms, HPEC18: IEEE High Performance Extreme Computing Conference, Best Paper Finalist, September 2018.

    Jacob B. Lambert, Seyong Lee, Jungwon Kim, and Jeffrey S. Vetter. High-Level Programming and Optimizations for High-Performance Computing with FPGAs, 32nd ACM International Conference on Supercomputing (ICS), Beijing, China, 2018.

    Ivy Bo Peng, Jeffrey S. Vetter, Shirley V. Moore, and Seyong Lee. Tuyere: Enabling Scalable Memory Workloads for System Exploration, Proceedings of the ACM Symposium on High-Performance and Distributed Computing (HPDC), Tempe, Arizona, USA, 2018.

    Pak Markthub, Mehmet E. Belviranli, Seyong Lee, Jeffrey S. Vetter, and Satoshi Matsuoka, Efficiently Enlarging GPU Memory Capacity with NVM, GPU Technology Conference, Poster, San Jose, California, USA, 2018.

    Mehmet E. Belviranli, Seyong Lee, Jeffrey S. Vetter, and Laxmi N. Bhuyan. Juggler: A Dependency-Aware Task Based Execution Framework for GPUs, Proceedings of ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), Vösendorf/Wien, Austria, 2018.

    Gregory Herschlag, Amanda Randles, Seyong Lee, and Jeffrey S. Vetter. GPU Data Access on Complex Geometries for D3Q19 Lattice Boltzmann Method, 32th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Vancouver, British Columbia, CANADA, 2018.

    Kaixi Hou, Hao Wang, Wu-chun Feng, Jeffrey S. Vetter, and Seyong Lee. Highly Efficient Compensation-based Parallelism for Wavefront Loops on GPUs, 32th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Vancouver, British Columbia, CANADA, 2018.

    Seyong Lee. A Framework for Directive-Based High-Performance Reconfigurable Computing, OpenACC for Programmers: Concepts and Strategies, Book Chapter, 2017.

    Jungwon Kim, Seyong Lee, and Jeffrey S. Vetter. PapyrusKV: A High-Performance Parallel Key-Value Store for Distributed NVM Architectures, SC17: ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, Colorado, USA, November 2017. (61/327, 18.6%)

    Michael Wolfe, Seyong Lee, Jungwon Kim, Xiaonan Tian, Rengan Xu, Sunita Chandrasekaran, and Barbara Chapman, Implementing the OpenACC Data Model, The Seventh International Workshop on Accelerators and Hybrid Exascale Systems (AsHES) in conjunction with IPDPS17, 2017.

    Joel E. Denny, Seyong Lee, and Jeffrey S. Vetter, Language-Based Optimizations for Persistence on Nonvolatile Main Memory Systems, 31th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2017.

    Jungwon Kim, Kittisak Sajjaponse, Seyong Lee, and Jeffrey S. Vetter, Design and Implementation of Papyrus: Parallel Aggregate Persistent Storage, 31th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2017.