Supercomputing Applications
           
Event Type Start Time End Time Rm # Chair  

 

Paper 3:30PM 4:00PM -- John Gustafson (affiliation)
 
Title:
Applications of Algebraic Multigrid to Large-Scale Finite Element Analysis of Whole Bone Micro-Mechanics on the IBM SP
  Speakers/Presenter:
Mark F. Adams (Sandia National Laboratories), Harun H. Bayraktar (University of California, Berkeley), Tony M. Keaveny (University of California, Berkeley), Panayiotis Papadopoulos (University of California, Berkeley)

 

Paper 4:00PM 4:30PM -- John Gustafson (affiliation)
 
Title:
Parallel Multilevel Sparse Approximate Inverse Preconditioners in Large Sparse Matrix Computations
  Speakers/Presenter:
Kai Wang (University of Kentucky), Jun Zhang (University of Kentucky), Chi Shen (University of Kentucky)

 

Paper 4:30PM 5:00PM -- John Gustafson (affiliation)
 
Title:
Parallel Particle-In-Cell Simulation of Colliding Beams in High Energy Accelerators
  Speakers/Presenter:
Ji Qiang (Lawrence Berkeley National Laboratory), Miguel A. Furman (Lawrence Berkeley National), Robert D. Ryne (Lawrence Berkeley National Laboratory)
             

 

     
  Session: Supercomputing Applications
  Title: Applications of Algebraic Multigrid to Large-Scale Finite Element Analysis of Whole Bone Micro-Mechanics on the IBM SP
  Chair: John Gustafson (affiliation)
  Time: Tuesday, November 18, 3:30PM - 5:00PM
  Rm #: --
  Speakers/Presenter:  
  Mark F. Adams (Sandia National Laboratories), Harun H. Bayraktar (University of California, Berkeley), Tony M. Keaveny (University of California, Berkeley), Panayiotis Papadopoulos (University of California, Berkeley)
   
  Description:
  Multigrid is well known to be a highly scalable linear solver for elasticity problems and is a natural choice for the analysis of large-scale finite element models of whole bones. We present some of the first applications of scalable linear solver algorithms on massively parallel computers to whole vertebral body structural analysis with over 135 million elements. We analyze the performance of our algebraic multigrid (AMG) methods on problems with over 537 million degrees of freedom on IBM SP (LLNL and SDSC) parallel computers. We show excellent parallel scalability, both in the algorithms and the implementations, and analyze the nodal performance of the important AMG kernels on the IBM Power3 and Power4 architectures.
  Link: --
   

 

     
  Session: Supercomputing Applications
  Title: Parallel Multilevel Sparse Approximate Inverse Preconditioners in Large Sparse Matrix Computations
  Chair: John Gustafson (affiliation)
  Time: Tuesday, November 18, 3:30PM - 5:00PM
  Rm #: --
  Speakers/Presenter:  
  Kai Wang (University of Kentucky), Jun Zhang (University of Kentucky), Chi Shen (University of Kentucky)
   
  Further Information:
  We investigate the use of the multistep successive preconditioning strategies (MSP) to construct a class of parallel multilevel sparse approximate inverse (SAI) preconditioners. We do not use independent set ordering, but a diagonal dominance based matrix permutation to build a multilevel structure. The purpose of introducing multilevel structure into SAI is to enhance the robustness of SAI for solving difficult problems. Forward and backward preconditioning iteration and two Schur complement preconditioning strategies are proposed to improve the performance and to reduce the storage cost of the multilevel preconditioners. One version of the parallel multilevel SAI preconditioner based on the MSP strategy is implemented. Numerical experiments for solving a few sparse matrices on a distributed memory parallel computer are reported.
  Link: --
   

 

     
  Session: Supercomputing Applications
  Title: Parallel Particle-In-Cell Simulation of Colliding Beams in High Energy Accelerators
  Chair: John Gustafson (affiliation)
  Time: Tuesday, November 18, 3:30PM - 5:00PM
  Rm #: --
  Speakers/Presenter:  
  Ji Qiang (Lawrence Berkeley National Laboratory), Miguel A. Furman (Lawrence Berkeley National), Robert D. Ryne (Lawrence Berkeley National Laboratory)
   
  Further Information:
  In this paper we present a self-consistent simulation model of colliding beams in high energy accelerators. The model, which is based on a particle-in-cell method, uses a new developed shifted-Green function algorithm for the efficient calculation of the beam-beam interaction. In the parallel implementation we studied various strategies to deal with the particular nature of the colliding beam system -- a system in which there can be significant particle movement between beam-beam collisions. We chose a particle-field decomposition approach instead of the conventional domain decomposition or particle decomposition approach. The particle-field approach leads to good load balance, reduced communication cost, and shows the best scalability on an IBM SP3 among the three parallel implementations. A performance test of the beam-beam model on a Cray T3E, IBM SP3, and a PC cluster is presented. As an application, we studied the effect of long-range collisions on antiproton lifetime in the Fermilab Tevatron.
  Link: --