Overview

AMReX

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Andrew Myers

Contact Information Andrew Myers MS 50A-3111 Lawrence Berkeley National Lab 1 Cyclotron Rd. Berkeley, CA 94720 510-486-6900 (fax) [email protected]

I am a member of the Center for Computational Sciences and Engineering (CCSE) at the Lawrence Berkeley National Laboratory (LBNL). My current research focuses on the design and implementation of scalable parallel algorithms for conducting particle and particle-mesh simulations on current and upcoming supercomputing architectures, particularly in the context of adaptive mesh refinement. These algorithms have applications to the modelling of, for example, large-scale structure formation in cosmology, plasma acceleration in particle accelerators, and the solids phase in multi-phase flow problems.

More generally, I am interested in parallel algorithms for scientific computing (particularly for GPU platforms), particle methods, and the visualization and analysis of large simulation datasets.

Much of my work is open source and can be followed on my Github page.

Particles in AMReX

I am the lead developer of the particle library in AMReX, a software framework for building massively parallel block-structured adaptive mesh refinement (AMR) applications that is supported by the Exascale Computing Project (ECP). Particles are used in some capacity by most of the AMReX application codes, including six of the ECP application development projects. In AMReX, we are particularly interested in particles that live on and interact with a constantly-changing hierarchy of refinement patches, which adds an additional layer of complication to the underyling data structures. AMReX provides methods for handling the MPI communication of particle data, including both redistribution and halo exchange, as well as implementations of several common operations used in particle applications, such as neighbor list construction, particle-mesh deposition and interpolation, reductions, etc. Much of my recent work has focused on re-working the particle data structures and algorithms for hybrid CPU/GPU platforms, such as OLCF's Summit machine. AMReX application codes involving significant particle work have been demonstrated to scale well up to the full machine, and have demonstrated good speed-ups over CPU-only platforms.

Plasma and laser wakefield acceleration with WarpX

I am also a member of the ECP-funded WarpX project, which is collaboration between CCSE and the Accelerator Modelling group at LBNL, Livermore Lab, and the Stanford Linear Accelerator Center. The goal of this project is to build a new simulation tool for studying plasma- and laser- driven wakefield acceleration, a process by which charged particles are accelerated over much shorter distances than in conventional accelerators. The hope is that, by harnessing the power of future exascale computers, WarpX can aid in the design of smaller, less costly particle accelerators. WarpX is a relativistic, electromagnetic Particle-in-Cell code that includes several advanced features, such as spectral Maxwell solvers, perfectly-matched absorbing layers, mesh refinement, ionization, and the ability to operate in a boosted reference frame. Along with MFIX-Exa, it is one of the primary drivers of development for the AMReX particle library.

I completed my PhD in Physics at the University of California at Berkeley in September 2013, working with Richard Klein and Christopher McKee on the topics of high-mass star formation and the interstellar medium. Later, I was a postdoctoral researcher in the Applied Numerical Algorithms Group at LBNL, where I worked on various mathematical topics related to the convergence of particle-in-cell schemes for Vlasov-Poisson problems. You can read about this work in my publications below. Finally, I have also been active in the open-source scientific Python community, in particular with the yt project, and still retain interests in large-scale scientific visualization and data analysis.

• Andrew Myers, Weiqun Zhang, Ann Almgren, Thierry Antoun, John Bell, Axel Huebl and Alexander Sinn, AMReX and pyAMReX: Looking Beyond ECP, International Journal of High Performance Computing Applications , August 2024, [doi]
• Scott Atchley et. al., Frontier: Exploring Exascale. accepted for publication at Supercomputing 2023,
• A. Lattanzi, W. Fullmer, A. Myers, J. Musser, Towards polydisperse flows with MFIX-Exa. ASME. J. Fluids Eng, 23 January 2024. [doi].
• H. Klion, R. Jambunathan, M. E. Rowan, E. Yang, D. Willcox, J.-L. Vay, R. Lehe, A. Myers, A. Huebl, W. Zhang, Particle-in-Cell Simulations of Relativistic Magnetic Reconnection with Advanced Maxwell Solver Algorithms. The Astrophysical Journal, 925, 1, 2023. [arxiv]
• Bruce J. Palmer, Ann S. Almgren, Connah G.M. Johnson, Andrew T Myers, and William R. Cannon, BMX: Biological Modelling and interface eXchange, Nature Scientific Reports, 13, July 2023. [doi]
• Luca Fedeli, Axel Huebl, France Boillod-Cerneux, Thomas Clark, Kevin Gott, Conrad Hillairet, Stephan Jaure, Adrien Leblanc, Remi Lehe, Andrew Myers, Christelle Piechurski, Mitsuhisa Sato, Neil Zaim, Weiqun Zhang, Jean-Luc Vay, Henri Vincenti, Pushing the frontier in the design of laser-based electron accelerators with groundbreaking mesh-refined particle-in-cell simulations on exascale-class supercomputers, SC '22: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, November 2022, Article No.: 3, Pages 1-12 [doi]
• Severin Diederichs, Carlo Benedetti, Axel Huebl, Remi Lehe, Andrew Myers, Alexander Sinn, Jean-Luc Vay, Weiqun Zhang, Maxence Thevenet, HiPACE++: a portable, 3D quasi-static Particle-in-Cell code, Computer Physics Communications, 278, 108421, 2022. [link][arXiv]
• Jean Sexton, Zarija Lukic, Ann Almgren, Chris Daley, Brian Friesen, Andrew Myers, and Weiqun Zhang, Nyx: A Massively Parallel AMR Code for Computational Cosmology, Journal of Open Source Software, 6(63), 3068, 2021. [doi]
• L. Fedeli, A. Sainte-Marie, N. Zaim, M. Thevenet, J. L. Vay, A. Myers, F. Quere, and H. Vincenti, Probing strong-field QED with Doppler-boosted petawatt-class lasers, accepted by Physical Review Letters, May 10, 2021, [PRL]
• Sherwood Richers, Don E. Willcox, Nicole M. Ford, and Andrew Myers, Particle-in-cell simulation of the neutrino fast flavor instability, Physical Review D, April 20, 2021, [doi]
• Jordan Musser, Ann S Almgren, William D Fullmer, Oscar Antepara, John B Bell, Johannes Blaschke, Kevin Gott, Andrew Myers, Roberto Porcu, Deepak Rangarajan, Michele Rosso, Weiqun Zhang, and Madhava Syamlal, MFIX:Exa: A Path Towards Exascale CFD-DEM Simulations, The International Journal of High Performance Computing Applications, April 16, 2021. [IJHPCA] [doi]
• Weiqun Zhang, Andrew Myers, Kevin Gott, Ann Almgren and John Bell, AMReX: Block-Structured Adaptive Mesh Refinement for Multiphysics Applications, The International Journal of High Performance Computing Applications, June 12, 2021. [IJHPCA] [doi]
• J-L Vay, Ann Almgren, LD Amorim, John Bell, L Fedeli, L Ge, K Gott, DP Grote, M Hogan, A Huebl, R Jambunathan, R Lehe, A Myers, C Ng, M Rowan, O Shapoval, M Thevenet, H Vincenti, E Yang, N Zaim, W Zhang, Y Zhao and E Zoni, Modeling of a chain of three plasma accelerator stages with the WarpX electromagnetic PIC code on GPUs, Physics of Plasmas, 28(2), 2021. [doi]
• Andrew Myers, Ann Almgren, Diana Almorim, John Bell, Luca Fedeli, Lixin Ge, Kevin Gott, David Grote, Mark Hogan, Axel Huebl, Revathi Jambunathan, Remi Lehe, Cho Ng, Michael Rowan, Olga Shapoval, Maxence Thevenet, Jean-Luc Vay, Henri Vincenti, Eloise Yang, Neil Zaim, Weiqun Zhang, Yin Zhao, Edoardo Zoni, Porting WarpX to GPU-accelerated platforms, accepted by Parallel Computing, 2021. [arxiv]
• Y. Zhao, R. Lehe, A. Myers, M. Thevenet, A. Huebl, C. B. Schroeder, and J.-L. Vay, Modeling of emittance growth due to Coulomb collisions in plasma-based accelerators, Physics of Plasmas, October, 2020. [doi]
• W Zhang, A Almgren, V Beckner, J Bell, J Blashke, C Chan, M Day, B Friesen, K Gott, D Graves, M Katz, A Myers, T Nguyen, A Nonaka, M Rosso, S Williams, M Zingale, AMReX: a framework for block-structured adaptive mesh refinement, Journal of Open Source Software, May 2019
• B Loring, A Myers, D Camp, EW Bethel, Python-based in situ analysis and visualization Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV 18, ACM Press, 2018
• JL Vay, A Almgren, J Bell, L Ge, DP Grote, M Hogan, O Kononenko, R Lehe, A Myers, C Ng, J Park, R Ryne, O Shapoval, M Thevenet, W Zhang, Warp-X: A new exascale computing platform for beam-plasma simulations, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2018, 909:476--479
• M Krumholz, A Myers, R Klein, C McKee, What Physics Determines the Peak of the IMF? Insights from the Structure of Cores in Radiation-Magnetohydrodynamic Simulations, MNRAS, May 19, 2016
• A Myers, P Colella, B Van Straalen, A 4th-Order Particle-in-Cell Method with Phase-Space Remapping for the Vlasov-Poisson Equation, SIAM Journal on Scientific Computing, Volume 39, No 3, pp. B467-B485, May 9, 2017
• A Myers, P Colella, B Van Straalen, The Convergence of Particle-in-Cell Schemes for Cosmological Dark Matter Simulations, The Astrophysical Journal, Volume 816, Issue 2, article id. 56, 2016
• A Myers, C McKee, PS Li, The CH+ abundance in turbulent, diffuse molecular clouds, Monthly Notices of the Royal Astronomical Society, Volume 453, Issue 3, p.2747-2758, November 1, 2015
• A Myers, R Klein, M Krumholz, C McKee, Star cluster formation in turbulent, magnetized dense clumps with radiative and outflow feedback, Monthly Notices of the Royal Astronomical Society, Volume 439, Issue 4, p.3420-3438, April 1, 2014
• A Myers, C McKee, A Cunningham, R Klein, M Krumholz, The Fragmentation of Magnetized, Massive Star-forming Cores with Radiative Feedback, The Astrophysical Journal, Volume 766, Issue 2, article id. 97, April 1, 2013
• PS Li, A Myers, C McKee, Ambipolar Diffusion Heating in Turbulent Systems, The Astrophysical Journal, Volume 760, Issue 1, article id. 33, November 1, 2012
• A Myers, M Krumholz, R Klein, C McKee, Metallicity and the Universality of the Initial Mass Function, The Astrophysical Journal, Volume 735, Issue 1, article id. 49, 2011

• Building Exascale-Ready Adaptive Mesh Refinement Applications with AMReX, ECP Annual Meeting, Virtual, 2021
• WarpX: Scalable Particle-in-Cell Algorithms for Emerging Architectures with AMReX. SIAM Conference on Computational Science and Engineering, Fort Worth, TX, 2021
• AMReX and applications on GPUs - lessons learned from Summit. Joint SIAM / CAIMS Annual Meeting, Toronto, Ontario, Canada, 2020
• An overview of particles in AMReX, SIAM Conference on Parallel Processing, Seattle, Washington, 2020
• Introduction to AMReX - a new framework for block-structured adaptive mesh refinement calculations, Advanced Modelling and Simulation Seminar Series, Nasa Ames Research Center, 2018
• A high-order accurate Particle-in-Cell method for Vlasov-Poisson problems over long time integrations, Advanced Modelling and Simulation Seminar Series, Nasa Ames Research Center, 2016
• Controlling Numerical Error in Particle-in-Cell Simulations of Collisionless Dark Matter, SIAM Conference on Computational Science and Engineering, Salt Lake City, Utah, 2015
• Radiation-Magnetohydrodynamic Simulations of Star Formation, Friday Lunch Time Astrophysics Seminar, UC - Santa Cruz, 2014
• The Fragmentation of High-Mass Dense Cores, Planet and Star Formation Seminar, UC - Berkeley, 2013

• M Thevenet, J-L Vay, A Almgren, D Amorim, J Bell, A Heubl, R Jambunathan, R Lehe, A Myers, J Park, O Shapoval, W Zhang, L Ge, M Hogan, C Ng, D Grote, Toward Exascale modeling of Plasma Particle Accelerators on GPU , Supercomputing 2019, Denver, CO, 2019
• D Amorim, J-L Vay, A Almgren, J Bell, K Gott, A Heubl, R Jambunathan, R Lehe, A Myers, J Park, M Rowan, O Shapoval, M Thevenet, W Zhang, Y Zhao, L Ge, M Hogan, C Ng, D Grote, WarpX - Efficient modeling of plasma-based accelerators with mesh refinement , American Physical Society Division of Plasma Physics Annual Meeting, Fort Lauderdale, FL, 2019
• D Amorim, J-L Vay, A Almgren, J Bell, A Heubl, R Jambunathan, R Lehe, A Myers, J Park, O Shapoval, M Thevenet, W Zhang, L Ge, M Hogan, C Ng, D Grote, WarpX ECP project recent progress , International Conference on Numerical Simulation of Plasmas, Sante Fe, NM, 2019
• R Jambunathan, A Myers, D Wilcox, J-L Vay, A Almgren, D Amorim, J Bell, K Gott, A Heubl, R Lehe, J Park, M Rowan, O Shapoval, M Thevenet, W Zhang, L Ge, M Hogan, C Ng, D Grote, WarpX: Towards Exascale Modelling of Pulsar Magnetospheres , Connecting Micro and Macro Scales: Acceleration, Reconnection, and Dissipation in Astrophysical Plasmas, Kavli Institute for Theoretical Physics, Santa Barbara, CA, 2019
• A Myers, J Bell, A Almgren, V Beckner, J Blaschke, C Chan, M Day, B Friesen, K Gott, D Graves, M Katz, T Nguyen, A Nonaka, M Rosso, S Williams, W Zhang, M Zingale Overview of AMReX - a new framework for block-structured adaptive mesh refinement calculations, SIAM Conference on Computational Science and Engineering, Spokane, WA, 2019
• Y L Lin, A Almgren, B Friesen, A Myers Performance Study of GPU Offloading via CUDA, OpenACC, and OpenMP in AMReX, SIAM Conference on Computational Science and Engineering, Spokane, WA, 2019
• D Wilcox, D Kasen, A Almgren, A Myers, W Zhang, SedonaEx: A Monte Carlo Radiation Transfer Code for Astrophysical Events, SIAM Conference on Computational Science and Engineering, Spokane, WA, 2019
• K Gott, A Myers, W Zhang, An Overview of GPU Strategies for Porting Amrex-Based Applications to Next-generation HPC Systems, SIAM Conference on Computational Science and Engineering, Spokane, WA, 2019
• M Thevenet, J-L Vay, A Almgren, J Bell, R Lehe, A Myers, J Park, O Shapoval, W Zhang, L Ge, M Hogan, C Ng, D Grote, WarpX: Toward Exascale modeling of Plasma Particle Accelerators , Supercomputing 2018, Dallas, TX, 2018
• A Myers, A Cunningham, R Klein, M Krumholz, C McKee, Fragmentation of Magnetized, Massive Cores with Radiative Feedback Star Formation and the Interstellar Medium: Thirty-Five Years Later, Berkeley, CA, 2012