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Scalable Solvers Group

Mark Adams

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Mark F Adams
Staff Scientist

I received my Ph.D. in Civil Engineering, from U.C. Berkeley in 1998 and am a former student and postdoc with Jim Demmel  in the Computer Science Division, at U.C. Berkeley.  I work in the Scalable Solvers Group at Lawrence Berkeley National Laboratory, and as an adjunct research scientist in the Applied Physics and Applied Mathematics Department at Columbia University.


Research Interests:

My research interests are in large scale simulations, extreme-scale multigrid equation solvers, magnetohydrodynamics solvers for fusion plasmas (Tokamaks), structure preserving discretization methods for magnetized plasmas, and particle-in-cell methods for plasma physics applications.

I work as a developer in the PETSc numerical library, developing its algebraic multigrid (AMG) framework and support for kinetic discretization methods, and I added a Fokker-Planck in Landau form collision operator in the DMPlex framework in PETSc. I work with computational physicists at Princeton Plasma Physics Laboratory (PPPL) on kinetic and fluid codes for fusion energy sciences.


Selected Papers:


Awards:


Journal Articles

M. Adams, P. Wang, J. Merson, K. Huck, M. Knepley, "A performance portable, fully implicit Landau collision operator with batched linear solvers", SIAM Journal on Scientific Computing, January 1, 2025,

Modern accelerators use hierarchical parallel programming models that enable massive multithreading within a processing element (PE), with multiple PEs per device driven by traditional processes. Batching is a technique for exposing PE-level parallelism in algorithms that have traditionally run on MPI processes or multiple threads within a single process. Opportunities for batching arise in, for example, kinetic discretizations of magnetized plasmas where collisions are advanced in velocity space at each spatial point independently.
This paper builds on previous work on a high-performance, fully nonlinear, Landau collision operator by batching the linear solver, as well as batching the spatial point problems and adding new support for multiple grids for multiscale, multi-species problems. An anisotropic relaxation verification test that agrees well with previous published results and analytical models is presented. The performance results from NVIDIA A100 and AMD MI250X nodes are presented with hardware utilization analysis for each architecture. The entire implicit Landau operator time advance is implemented in Kokkos for performance portability, running entirely on the device and is available in the PETSc numerical library.

Daniel Finn, Matthew Knepley, Joseph Pusztay and Mark Adams, "A Numerical Study of Landau Damping with PETSc-PIC", CAMCoS, March 1, 2023, doi: 10.2140/camcos.2023.18.135

Mark Adams, Satish Balay, Oana Marin, Lois Curfman McInnes, Richard Tran Mills, Todd Munson, Hong Zhang, Junchao Zhang, Jed Brown, Victor Eijkhout, Jacob Faibussowitsch, Matthew Knepley, Fande Kong, Scott Kruger, Patrick Sanan, Barry F. Smith, Hong Zhang, "The PETSc Community as Infrastructure", May 1, 2022, 24, doi: 10.1109/MCSE.2022.3169974

The communities that develop and support open-source scientific software packages are crucial to the utility and success of such packages. Moreover, they form an important part of the human infrastructure that enables scientific progress. This article discusses aspects of the Portable Extensible Toolkit for Scientific Computation community, its organization, and technical approaches that enable community members to help each other efficiently and effectively.

J. V. Pusztay, M. G. Knepley, and M. F. Adams, "Conservative Projection Between FEM and Particle Bases", SIAM Journal on Scientific Computing, January 1, 2022, doi: https://doi.org/10.1137/21M145407

R. Mills, M.F. Adams, S. Balay, J. Brown, A. Dener, M. Knepley, S. Kruger, H. Morgan, T. Munson, K. Rupp, B. Smith, S. Zampini, H. Zhang, J. Zhang, Junchao, "Toward performance-portable PETSc for GPU-based exascale systems", Parallel Computing, December 1, 2021, 108, doi: 10.1016/j.parco.2021.102831

The Portable Extensible Toolkit for Scientific computation (PETSc) library delivers scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization. The PETSc design for performance portability addresses fundamental GPU accelerator challenges and stresses flexibility and extensibility by separating the programming model used by the application from that used by the library, and it enables application developers to use their preferred programming model, such as Kokkos, RAJA, SYCL, HIP, CUDA, or OpenCL, on upcoming exascale systems. A blueprint for using GPUs from PETSc-based codes is provided, and case studies emphasize the flexibility and high performance achieved on current GPU-based systems.

Mark Adams, Stephen Cornford, Daniel Martin, Peter McCorquodale, "Composite matrix construction for structured grid adaptive mesh refinement", Computer Physics Communications, November 2019, 244:35-39, doi: 10.1016/j.cpc.2019.07.006

MF Adams, E Hirvijoki, MG Knepley, J Brown, T Isaac, R Mills, "Landau Collision Integral Solver with Adaptive Mesh Refinement on Emerging Architectures", SIAM J. Sci. Comput., 2017, 39:C452--C465, doi: 10.1137/17M1118828

R Hager, J Lang, CS Chang, S Ku, Y Chen, SE Parker, MF Adams, "Verification of long wavelength electromagnetic modes with a gyrokinetic-fluid hybrid model in the XGC code", Physics of Plasmas, 2017, 24, doi: 10.1063/1.4983320

E Hirvijoki, MF Adams, "Conservative discretization of the Landau collision integral", Physics of Plasmas, 2017, 24, doi: 10.1063/1.4979122

Mark Adams, Jed Brown, Matt Knepley, Ravi Samtaney, "Segmental Refinement: A Multigrid Technique for Data Locality", SIAM J. Sci. Comput., 2016, 38:4,

M. F. Adams, R. Samtaney and A. Brandt, "Toward Textbook Multigrid Efficiency for Fully Implicit Resistive Magnetohydrodynamics", Journal of Computational Physics, January 1, 2010, 229:6208–19, doi: 10.1016/j.jcp.2010.04.024

Conference Papers

M.F. Adams, D.P. Brennan, M.G. Knepley, P. Wang, "Landau collision operator in the CUDA programming model applied to thermal quench plasmas", 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), July 15, 2022, doi: 10.1109/IPDPS53621.2022.00020

M. F. Adams, H. H. Bayraktar, T. M. Keaveny and P. Papadopoulos, "Ultrascalable Implicit Finite Element Analyses in Solid Mechanics with Over Half a Billion Degrees of Freedom", ACM/IEEE Proceedings of SC2004, November 1, 2004, 34, doi: https://doi.org/10.1109/SC.2004.62

Gordon Bell Award, Special category, SuperComputing 2004

Presentation/Talks

Mark Adams, Samuel Williams, HPGMG BoF - Introduction, HPGMG BoF, Supercomputing, November 2016,

Samuel Williams, Mark Adams, Brian Van Straalen, Performance Portability in Hybrid and Heterogeneous Multigrid Solvers, Copper Moutain, March 2016,

Mark Adams, Samuel Williams, Jed Brown, HPGMG, Birds of a Feather (BoF), Supercomputing, November 2014,

Reports

A. P. S. Bhalla, B. E. Griffith, M. G. Knepley, M. F. Adams, and R. D. Guy, "Scalable smoothing strategies for a geometric multigrid method for the immersed boundary equations", December 1, 2016, doi: https://doi.org/10.48550/arXiv.1612.02208

M. Adams, P. Colella, D. T. Graves, J.N. Johnson, N.D. Keen, T. J. Ligocki. D. F. Martin. P.W. McCorquodale, D. Modiano. P.O. Schwartz, T.D. Sternberg, B. Van Straalen, "Chombo Software Package for AMR Applications - Design Document", Lawrence Berkeley National Laboratory Technical Report LBNL-6616E, January 9, 2015,

Mark F. Adams, Jed Brown, John Shalf, Brian Van Straalen, Erich Strohmaier, Samuel Williams, "HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems", LBNL Technical Report, 2014, LBNL 6630E,