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Title: Parallel beam dynamics calculations on high performance computers

Abstract

Faced with a backlog of nuclear waste and weapons plutonium, as well as an ever-increasing public concern about safety and environmental issues associated with conventional nuclear reactors, many countries are studying new, accelerator-driven technologies that hold the promise of providing safe and effective solutions to these problems. Proposed projects include accelerator transmutation of waste (ATW), accelerator-based conversion of plutonium (ABC), accelerator-driven energy production (ADEP), and accelerator production of tritium (APT). Also, next-generation spallation neutron sources based on similar technology will play a major role in materials science and biological science research. The design of accelerators for these projects will require a major advance in numerical modeling capability. For example, beam dynamics simulations with approximately 100 million particles will be needed to ensure that extremely stringent beam loss requirements (less than a nanoampere per meter) can be met. Compared with typical present-day modeling using 10,000-100,000 particles, this represents an increase of 3-4 orders of magnitude. High performance computing (HPC) platforms make it possible to perform such large scale simulations, which require 10's of GBytes of memory. They also make it possible to perform smaller simulations in a matter of hours that would require months to run on a single processor workstation.more » This paper will describe how HPC platforms can be used to perform the numerically intensive beam dynamics simulations required for development of these new accelerator-driven technologies.« less

Authors:
;  [1];  [2]
  1. Accelerator Operations and Technology Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)
  2. (United States)
Publication Date:
OSTI Identifier:
21165587
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 391; Journal Issue: 1; Conference: 1996 computational accelerator physics conference, Williamsburg, VA (United States), 24-27 Sep 1996; Other Information: DOI: 10.1063/1.52387; (c) 1997 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
43 PARTICLE ACCELERATORS; ACCELERATOR DRIVEN TRANSMUTATION; ACCELERATORS; BEAM DYNAMICS; COMPUTER-AIDED DESIGN; COMPUTERIZED SIMULATION; NEUTRON SOURCES; PARTICLE BEAMS; PERFORMANCE

Citation Formats

Ryne, Robert, Habib, Salman, and Theoretical Division Los Alamos National Laboratory, Los Alamos, New Mexico 87545. Parallel beam dynamics calculations on high performance computers. United States: N. p., 1997. Web. doi:10.1063/1.52387.
Ryne, Robert, Habib, Salman, & Theoretical Division Los Alamos National Laboratory, Los Alamos, New Mexico 87545. Parallel beam dynamics calculations on high performance computers. United States. doi:10.1063/1.52387.
Ryne, Robert, Habib, Salman, and Theoretical Division Los Alamos National Laboratory, Los Alamos, New Mexico 87545. 1997. "Parallel beam dynamics calculations on high performance computers". United States. doi:10.1063/1.52387.
@article{osti_21165587,
title = {Parallel beam dynamics calculations on high performance computers},
author = {Ryne, Robert and Habib, Salman and Theoretical Division Los Alamos National Laboratory, Los Alamos, New Mexico 87545},
abstractNote = {Faced with a backlog of nuclear waste and weapons plutonium, as well as an ever-increasing public concern about safety and environmental issues associated with conventional nuclear reactors, many countries are studying new, accelerator-driven technologies that hold the promise of providing safe and effective solutions to these problems. Proposed projects include accelerator transmutation of waste (ATW), accelerator-based conversion of plutonium (ABC), accelerator-driven energy production (ADEP), and accelerator production of tritium (APT). Also, next-generation spallation neutron sources based on similar technology will play a major role in materials science and biological science research. The design of accelerators for these projects will require a major advance in numerical modeling capability. For example, beam dynamics simulations with approximately 100 million particles will be needed to ensure that extremely stringent beam loss requirements (less than a nanoampere per meter) can be met. Compared with typical present-day modeling using 10,000-100,000 particles, this represents an increase of 3-4 orders of magnitude. High performance computing (HPC) platforms make it possible to perform such large scale simulations, which require 10's of GBytes of memory. They also make it possible to perform smaller simulations in a matter of hours that would require months to run on a single processor workstation. This paper will describe how HPC platforms can be used to perform the numerically intensive beam dynamics simulations required for development of these new accelerator-driven technologies.},
doi = {10.1063/1.52387},
journal = {AIP Conference Proceedings},
number = 1,
volume = 391,
place = {United States},
year = 1997,
month = 2
}
  • Faced with a backlog of nuclear waste and weapons plutonium, as well as an ever-increasing public concern about safety and environmental issues associated with conventional nuclear reactors, many countries are studying new, accelerator-driven technologies that hold the promise of providing safe and effective solutions to these problems. Proposed projects include accelerator transmutation of waste (ATW), accelerator-based conversion of plutonium (ABC), accelerator-driven energy production (ADEP), and accelerator production of tritium (APT). Also, next-generation spallation neutron sources based on similar technology will play a major role in materials science and biological science research. The design of accelerators for these projects will requiremore » a major advance in numerical modeling capability. For example, beam dynamics simulations with approximately 100 million particles will be needed to ensure that extremely stringent beam loss requirements (less than a nanoampere per meter) can be met. Compared with typical present-day modeling using 10,000{endash}100,000 particles, this represents an increase of 3{endash}4 orders of magnitude. High performance computing (HPC) platforms make it possible to perform such large scale simulations, which require 10{close_quote}s of GBytes of memory. They also make it possible to perform smaller simulations in a matter of hours that would require months to run on a single processor workstation. This paper will describe how HPC platforms can be used to perform the numerically intensive beam dynamics simulations required for development of these new accelerator-driven technologies. {copyright} {ital 1997 American Institute of Physics.}« less
  • Faced with a backlog of nuclear waste and weapons plutonium, as well as an ever-increasing public concern about safety and environmental issues associated with conventional nuclear reactors, many countries are studying new, accelerator-driven technologies that hold the promise of providing safe and effective solutions to these problems. Proposed projects include accelerator transmutation of waste (ATW), accelerator-based conversion of plutonium (ABC), accelerator-driven energy production (ADEP), and accelerator production of tritium (APT). Also, next-generation spallation neutron sources based on similar technology will play a major role in materials science and biological science research. The design of accelerators for these projects will requiremore » a major advance in numerical modeling capability. For example, beam dynamics simulations with approximately 100 million particles will be needed to ensure that extremely stringent beam loss requirements (less than a nanoampere per meter) can be met. Compared with typical present-day modeling using 10,000-100,000 particles, this represents an increase of 3-4 orders of magnitude. High performance computing (HPC) platforms make it possible to perform such large scale simulations, which require 10`s of GBytes of memory. They also make it possible to perform smaller simulations in a matter of hours that would require months to run on a single processor workstation. This paper will describe how HPC platforms can be used to perform the numerically intensive beam dynamics simulations required for development of these new accelerator-driven technologies.« less
  • A parallel algorithm has been designed for SHELXD to solve the heavy-atom partial structures of protein crystals quickly. Based on this algorithm, a program has been developed to run on high-performance multiple-CPU Linux PCs, workstations or clusters. Tests on the 32-CPU Linux cluster at SER-CAT, APS, Argonne National Laboratory, show that the parallelization dramatically speeds up the process by a factor of roughly the number of CPUs applied, leading to reliable and instant heavy-atom sites solution, which provides the practical opportunity to employ heavy-atom search as an alternative tool for anomalous scattering data quality evaluation during single/multiple-wavelength anomalous diffraction (SAD/MAD)more » data collection at synchrotron beamlines.« less
  • A message passing interface (MPI)-based implementation (Autodock4.lga.MPI) of the grid-based docking program Autodock4 has been developed to allow simultaneous and independent docking of multiple compounds on up to thousands of central processing units (CPUs) using the Lamarkian genetic algorithm. The MPI version reads a single binary file containing precalculated grids that represent the protein-ligand interactions, i.e., van der Waals, electrostatic, and desolvation potentials, and needs only two input parameter files for the entire docking run. In comparison, the serial version of Autodock4 reads ASCII grid files and requires one parameter file per compound. The modifications performed result in significantly reducedmore » input/output activity compared with the serial version. Autodock4.lga.MPI scales up to 8192 CPUs with a maximal overhead of 16.3%, of which two thirds is due to input/output operations and one third originates from MPI operations. The optimal docking strategy, which minimizes docking CPU time without lowering the quality of the database enrichments, comprises the docking of ligands preordered from the most to the least flexible and the assignment of the number of energy evaluations as a function of the number of rotatable bounds. In 24 h, on 8192 high-performance computing CPUs, the present MPI version would allow docking to a rigid protein of about 300K small flexible compounds or 11 million rigid compounds.« less
  • The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - 1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory,more » 2) minimizing the amount of code that must be ported for efficient acceleration, 3) utilizing the available processing power from both many-core CPUs and accelerators, and 4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.« less