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In this paper, we present an object-oriented three-dimensional parallel particle-in-cell code for beam dynamics simulation in linear accelerators. A two-dimensional parallel domain decomposition approach is employed within a message passing programming paradigm along with a dynamic load balancing. Implementing object-oriented software design provides the(More)
We describe OSIRIS, a three-dimensional, relativistic, massively parallel, object oriented particle-in-cell code for modeling plasma based accelerators. Developed in Fortran 90, the code runs on multiple platforms (Cray T3E, IBM SP, Mac clusters) and can be easily ported to new ones. Details on the code's capabilities are given. We discuss the(More)
Object-oriented techniques promise to improve the software design and programming process by providing an application-oriented view of programming while facilitating modification and reuse. Since the software design crisis is particularly acute in parallel computation, these techniques have stirred the interest of the scientific parallel computing(More)
Keywords: Graphics processing unit (GPU) Computer unified device architecture (CUDA) Particle-in-cell (PIC) plasma simulation a b s t r a c t We present an implementation of a 2D fully relativistic, electromagnetic particle-in-cell code, with charge-conserving current deposition, on parallel graphics processors (GPU) with CUDA. The GPU implementation(More)
We illustrate how Fortran 90 supports object-oriented concepts by example of plasma particle computations on the IBM SP. Our experience shows that Fortran 90 and object-oriented methodology give high performance while providing a bridge from Fortran 77 legacy codes to modern programming principles. All of our object-oriented Fortran 90 codes execute more(More)
Emerging computer architectures consist of an increasing number of shared memory computing cores in a chip, often with vector (SIMD) co-processors. Future exascale high performance systems will consist of a hierarchy of such nodes, which will require different algorithms at different levels. Since no one knows exactly how the future will evolve, we have(More)