Title :
PIConGPU: A Fully Relativistic Particle-in-Cell Code for a GPU Cluster
Author :
Burau, Heiko ; Widera, Renée ; Hönig, Wolfgang ; Juckeland, Guido ; Debus, Alexander ; Kluge, Thomas ; Schramm, Ulrich ; Cowan, Tomas E. ; Sauerbrey, Roland ; Bussmann, Michael
Author_Institution :
Forschungszentrum Dresden-Rossendorf e.V., Dresden, Germany
Abstract :
The particle-in-cell (PIC) algorithm is one of the most widely used algorithms in computational plasma physics. With the advent of graphical processing units (GPUs), large-scale plasma simulations on inexpensive GPU clusters are in reach. We present an implementation of a fully relativistic plasma PIC algorithm for GPUs based on the NVIDIA CUDA library. It supports a hybrid architecture consisting of single computation nodes interconnected in a standard cluster topology, with each node carrying one or more GPUs. The internode communication is realized using the message-passing interface. The simulation code PIConGPU presented in this paper is, to our knowledge, the first scalable GPU cluster implementation of the PIC algorithm in plasma physics.
Keywords :
graphical user interfaces; hybrid simulation; message passing; physics computing; plasma simulation; relativistic plasmas; GPU Cluster; NVIDIA CUDA library; PIConGPU; computation nodes; computational plasma physics; graphical processing units; hybrid architecture; internode communication; large-scale plasma simulations; message-passing interface; particle-in-cell code; relativistic plasma PIC algorithm; standard cluster topology; Clustering algorithms; Computational modeling; Computer architecture; Graphics processing unit; Instruction sets; Magnetic cores; Plasmas; Electron accelerators; parallel algorithms; parallel architectures; particle beams; plasma waves; simulation software;
Journal_Title :
Plasma Science, IEEE Transactions on
DOI :
10.1109/TPS.2010.2064310
