Daniel Quinlan is a Distinguished Member of Technical Staff at Lawrence Livermore National Laboratory (LLNL), where he serves as the long-time project leader of the ROSE compiler infrastructure. Over a career spanning more than three decades, Dr. Quinlan has made foundational contributions to the fields of compiler technology, parallel scientific computing, and software engineering. ROSE, his flagship project, began as a one-person effort and has since evolved into a robust and collaborative infrastructure supporting over 20 internally funded and externally facing projects, with broad impact.

His research interests span compiler design, source-to-source transformation, program analysis, software assurance, performance tuning, cybersecurity, and domain-specific languages. ROSE supports a broad range of programming languages—including C, C++, Fortran, CUDA, OpenCL, and UPC—and serves as the foundation for a variety of analysis and transformation tools in both classified and open-source contexts.

Dr. Quinlan earned his Ph.D. in Applied Mathematics from the University of Colorado at Denver, where he was recognized as the Most Outstanding Graduate Student. He began his national laboratory career at Los Alamos National Laboratory (LANL), where his early work focused on parallel adaptive mesh refinement and object-oriented numerical frameworks. He moved to LLNL in 1998, where he has since advanced both the scale and scientific impact of compiler-enabled toolchains.

A deeply committed mentor and collaborator, Dr. Quinlan has supervised over 100 students and postdoctoral researchers, many of whom now hold influential positions in academia and industry. He has delivered invited talks at high-profile venues including Google TechTalks and C++Now, and has served on program committees for leading conferences such as IPDPS, PACT, and PADTAD.

In recognition of his exceptional contributions to LLNL’s scientific mission, Dr. Quinlan was promoted in 2022 to Distinguished Member of Technical Staff, the highest technical honor awarded to scientists and engineers at the laboratory.

Ph.D., Applied Mathematics, University of Colorado at Denver, Denver, CO; Most Outstanding Graduate Student; Dissertation: Parallel Adaptive Mesh Refinement

B.A., Applied Mathematics, University of Colorado at Denver, Denver, CO; Graduated Summa Cum Laude

Recent and Representative

• Nguyen, T. et al. (2017). Automatic translation of MPI source into a latency-tolerant, data-driven form. Journal of Parallel and Distributed Computing, Vol. 6.
• Vanderbruggen, T. et al. (2017). Directive-based tile abstraction to distribute loops on accelerators. GPGPU-10, Austin, TX.
• Schordan, M. et al. (2016). Automatic generation of reversible C++ code and its performance in a scalable kinetic monte carlo application. SIGSIM-PADS 2016.
• Milewicz, R. et al. (2016). Lightweight runtime checking of C programs with RTC. Journal on Computer Languages, Systems and Structures, Elsevier.
• Lin, P.-H. et al. (2016). Automatically Optimizing Stencil Computations on Many-core NUMA Architectures. LCPC 2016.
• Liao, C. et al. (2015). Enhancing domain specific language implementations through ontology. WOLFHPC '15.
• Yan, Y. et al. (2015). Supporting multiple accelerators in high-level programming models. PMAM '15.

Dr. Quinlan also has an extensive publication record with over 100 papers spanning four decades, covering topics including object-oriented design for adaptive mesh refinement, compiler-based optimization, program verification, performance engineering, binary analysis, and cave exploration.

• 2022 – Promotion to Distinguished Member of Technical Staff (DMTS), LLNL
• 2012 – Individual Performance Award, LLNL Computation Directorate
• 2010 – Directorate Award, Global Security, LLNL
• 2009 – Computation Directorate Noteworthy Achievement Award, LLNL
• 2009 – R&D 100 Award for the ROSE Compiler Project
• 2008 – Best Paper Award, PATDAD Conference
• 1994 – DOE Postdoctoral Fellowship, Los Alamos National Laboratory
  • Research area: Object-Oriented design for Adaptive Mesh Refinement and Overlapping Grid solution methods.
• 1993–1994 – Director’s Funded Postdoctoral Fellowship, Los Alamos National Laboratory
  • Research area: Object-Oriented design for Adaptive Mesh Refinement.
• 1993 – Most Outstanding Graduate Student, University of Colorado at Denver
• 1989–1992 – NASA Graduate Student Research Fellowship
  • Developed scalable parallel adaptive mesh refinement technology for hypersonic flow problems.
• 1991 – Winner, SIAM Student Paper Competition, Copper Mountain Multigrid Conference
• 1987 – Graduated Summa Cum Laude, University of Colorado at Denver
• 1987 – National Champion, ORSA Mathematical Modeling Competition
• 1977 – 3rd Place, Kentucky State Mathematics Competition
• 1972 – 1st Place, Ontario Junior Archery Championships, Canada