Axel Huebl, a research scientist in the Advanced Modeling Program (AMP) in the Accelerator Technology & Applied Physics Division at Lawrence Berkeley National Laboratory (Berkeley Lab), has received the National Energy Research Scientific Computing (NERSC) Center Early Career Award for Innovative Use of High-Performance Computing (HPC).
The award recognizes his early career research in computational accelerator physics, particularly his leadership in establishing innovative modeling techniques that utilize graphics processing units (GPUs) for accelerated high-performance computing, high-fidelity modeling to train data (Machine Learning, or ML) models, and seamlessly coupling the trained models into GPU-accelerated beamline models to bridge time and space scales.
Huebl said, “I am honored and thrilled to receive the award, which acknowledges my contributions and early career leadership in computational accelerator physics. The AMP team’s approach to conducting research embodies Berkeley Lab’s core value of team science and building bridges between physics modeling, computing, and data science and drive my research.”
“My work,” he continues, “brings together my expertise in accelerator modeling, my involvement with advanced open-source scientific software for the high-performance computing community, and my mentoring and training of students, interns, and postdocs.”
(l-r) Ryan Sandeberg, Jean-Luc Vay, and Axel Huebl from ATAP’s Advanced Modeling Program.
The new particle accelerator simulation techniques being developed by Huebl and the AMP team create a tightly coupled synergy between HPC and ML models in simulations. “Establishing fully GPU-accelerated integration of cutting-edge HPC and data-driven modeling is a new direction,” noted Huebl. “Leveraging this work and other ML techniques, we are working on new approaches that expand into rapid control, fast optimizations, and research towards digital twins of accelerators.”
Huebl was also a key member of an international team of multidisciplinary researchers led by AMP Head Jean-Luc Vay that won the Association for Computing Machinery’s 2022 Gordon Bell Prize. This prestigious award recognizes outstanding achievements in high-performance computing applied to challenges in science, engineering, and large-scale data analytics. It has the potential to revolutionize radiotherapy treatments and lead to significant advancements for the next generation of particle accelerators dedicated to high-energy physics and other applications.
To learn more …
Bridging the Gap in Advanced Accelerator Modeling
Myers, A., Zhang, W., Almgren, A., Antoun, T., Bell, J., Huebl, A., and Sinn, A. “AMReX and pyAMReX: Looking beyond the exascale computing project,” The International Journal of High-Performance Computing Applications, 2024. https://doi.org/10.1177/10943420241271017
Sandberg, R. T., Lehe, R., Mitchell, C. E., Garten, M., Myers, A., Qiang, J., Vay, J.-L., and Huebl, A. “Synthesizing Particle-in-Cell Simulations Through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines,” Proc. of Platform for Advanced Scientific Computing (PASC’24), PASC24 Best Paper award & keynote, 2024. https://doi.org/10.1145/3659914.3659937
Huebl, A., Ananthan, S., Grote, D. P., Sandberg, R. T., Zoni, E., Jambunathan, R., Lehe, R., Myers, A., and Zhang, W. “pyAMReX: GPU-Enabled, Zero-Copy AMReX Python Bindings including AI/ML software,” 2023. https://doi.org/10.5281/zenodo.8408733 https://github.com/AMReX-Codes/pyamrex
Sandberg R. T., Lehe R., Mitchell C. E., Garten M., Qiang J., Vay J.-L., and Huebl A. “Hybrid Beamline Element ML-Training for Surrogates in the ImpactX Beam-Dynamics Code,” 14th International Particle Accelerator Conference (IPAC’23), WEPA101, 2023. https://doi.org/10.18429/JACoW-IPAC2023-WEPA101
Huebl, A., Lehe, R., Mitchell, C. E., Qiang, J., Ryne, R. D., Sandberg, R. T., and Vay, J.-L. “Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale,” 2022 North American Particle Accelerator Conference (NAPAC’22), 2022. https://doi.org/10.18429/JACoW-NAPAC2022-TUYE2
Fedeli, L., Huebl, A., et al. “Pushing the Frontier in the Design of Laser-Based Electron Accelerators with Groundbreaking Mesh-Refined Particle-In-Cell Simulations on Exascale-Class,” Supercomputers. SC22: International Conference for High-Performance Computing, Networking, Storage and Analysis, 2022 (Gordon Bell Prize Winner). https://doi.org/10.1109/SC41404.2022.00008
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