NAPAC2022 - List of Authors (Vay, J.-L.)

Paper	Title	Page
TUYE2	Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale	302
	A. Huebl, R. Lehé, C.E. Mitchell, J. Qiang, R.D. Ryne, R.T. Sandberg, J.-L. Vay LBNL, Berkeley, California, USA
	Funding: Work supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. DOE SC and the NNSA, resources of NERSC, and by LBNL LDRD under DOE Contract DE-AC02-05CH11231. Particle accelerators are among the largest, most complex devices. To meet the challenges of increasing energy, intensity, accuracy, compactness, complexity and efficiency, increasingly sophisticated computational tools are required for their design and optimization. It is key that contemporary software take advantage of the latest advances in computer hardware and scientific software engineering practices, delivering speed, reproducibility and feature composability for the aforementioned challenges. A new open source software stack is being developed at the heart of the Beam pLasma Accelerator Simulation Toolkit (BLAST) by LBNL and collaborators, providing new particle-in-cell modeling codes capable of exploiting the power of GPUs on Exascale supercomputers. Combined with advanced numerical techniques, such as mesh-refinement, and intrinsic support for machine learning, these codes are primed to provide ultrafast to ultraprecise modeling for future accelerator design and operations. [1] J.-L. Vay, A. Huebl, et al, Phys. Plasmas 28, 023105 (2021) [2] J.-L. Vay, A. Huebl, et al, J. Instr. 16, T10003 (2021) [3] A. Myers, et al (incl. A. Huebl), Parallel Comput. 108, 102833 (2021)
	Slides TUYE2 [9.399 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-TUYE2
About •	Received ※ 13 July 2022 — Revised ※ 02 August 2022 — Accepted ※ 08 August 2022 — Issue date ※ 11 August 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale

302

A. Huebl, R. Lehé, C.E. Mitchell, J. Qiang, R.D. Ryne, R.T. Sandberg, J.-L. Vay
LBNL, Berkeley, California, USA

Funding: Work supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. DOE SC and the NNSA, resources of NERSC, and by LBNL LDRD under DOE Contract DE-AC02-05CH11231.
Particle accelerators are among the largest, most complex devices. To meet the challenges of increasing energy, intensity, accuracy, compactness, complexity and efficiency, increasingly sophisticated computational tools are required for their design and optimization. It is key that contemporary software take advantage of the latest advances in computer hardware and scientific software engineering practices, delivering speed, reproducibility and feature composability for the aforementioned challenges. A new open source software stack is being developed at the heart of the Beam pLasma Accelerator Simulation Toolkit (BLAST) by LBNL and collaborators, providing new particle-in-cell modeling codes capable of exploiting the power of GPUs on Exascale supercomputers. Combined with advanced numerical techniques, such as mesh-refinement, and intrinsic support for machine learning, these codes are primed to provide ultrafast to ultraprecise modeling for future accelerator design and operations.
[1] J.-L. Vay, A. Huebl, et al, Phys. Plasmas 28, 023105 (2021)
[2] J.-L. Vay, A. Huebl, et al, J. Instr. 16, T10003 (2021)
[3] A. Myers, et al (incl. A. Huebl), Parallel Comput. 108, 102833 (2021)

Slides TUYE2 [9.399 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-TUYE2

About •

Received ※ 13 July 2022 — Revised ※ 02 August 2022 — Accepted ※ 08 August 2022 — Issue date ※ 11 August 2022

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)