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Xavier Saez, Alejandro Soba, Edilberto Sanchez, Mervi Mantsinen, Jose M. Cela
PIC methods are one of the most used methods in plasma simulations. We present a comprehensible evaluation of the PIC code performance on four current parallel platforms: IBM PowerPC, Intel Nehalem (SMP), Intel Sandy Bridge (SMP) and ARM GPU. The behavior of computational algorithms and data structures are analyzed to deduce which code optimizations will […]
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T. Takaki, R. Rojas, M Ohno, T. Shimokawabe, T. Aoki
A GPU code has been developed for a phase-field lattice Boltzmann (PFLB) method, which can simulate the dendritic growth with motion of solids in a dilute binary alloy melt. The GPU accelerated PFLB method has been implemented using CUDA C. The equiaxed dendritic growth in a shear flow and settling condition have been simulated by […]
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Mu Wang, John F. Brady
In this work we develop the Spectral Ewald Accelerated Stokesian Dynamics (SEASD), a novel computational method for dynamic simulations of polydisperse colloidal suspensions with full hydrodynamic interactions. SEASD is based on the framework of Stokesian Dynamics (SD) with extension to compressible solvents, and uses the Spectral Ewald (SE) method [Lindbo & Tornberg, J. Comput. Phys. […]
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J. Sa, B. Noh, H. Kim, D. Choi, S. Lee, Y. Chung, D. Kim, H. Jang
Recently, many particle physics applications can be parallelized by using multicore platforms such as CPU and GPU. In this paper, we propose a parallel processing approach for Quantum ChromoDynamics(QCD) application by using both CPU and GPU. Instead of distributing the parallelizable workload to either CPU or GPU, we distribute the workload simultaneously into both CPU […]
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Gilbert Louis Bernstein, Chinmayee Shah, Crystal Lemire, Zachary DeVito, Matthew Fisher, Philip Levis, Pat Hanrahan
Designing programming environments for physical simulation is challenging because simulations rely on diverse algorithms and geometric domains. These challenges are compounded when we try to run efficiently on heterogeneous parallel architectures. We present Ebb, a domain-specific language (DSL) for simulation, that runs efficiently on both CPUs and GPUs. Unlike previous DSLs, Ebb uses a three-layer […]
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Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder
RUMD is a general purpose, high-performance molecular dynamics (MD) simulation package running on graphical processing units (GPU’s). RUMD addresses the challenge of utilizing the many-core nature of modern GPU hardware when simulating small to medium system sizes (roughly from a few thousand up to hundred thousand particles). It has a performance that is comparable to […]
Naser Sedaghati, Te Mu, Louis-Noel Pouchet, Srinivasan Parthasarathy, P. Sadayappan
Sparse matrix-vector multiplication (SpMV) is a core kernel in numerous applications, ranging from physics simulation and large-scale solvers to data analytics. Many GPU implementations of SpMV have been proposed, targeting several sparse representations and aiming at maximizing overall performance. No single sparse matrix representation is uniformly superior, and the best performing representation varies for sparse […]
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Christopher D. Cooper, Lorena A. Barba
Interactions between surfaces and proteins occur in many vital processes and are crucial in biotechnology: the ability to control specific interactions is essential in fields like biomaterials, biomedical implants and biosensors. In the latter case, biosensor sensitivity hinges on ligand proteins adsorbing on bioactive surfaces with a favorable orientation, exposing reaction sites to target molecules. […]
Axel Modave, Amik St-Cyr, Wim A. Mulder, Tim Warburton
Improving both accuracy and computational performance of numerical tools is a major challenge for seismic imaging and generally requires specialized implementations to make full use of modern parallel architectures. We present a computational strategy for reverse-time migration (RTM) with accelerator-aided clusters. A new imaging condition computed from the pressure and velocity fields is introduced. The […]
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Fang Liu, Nathan Luehr, Heather J. Kulik, Todd J. Martinez
The conductor-like polarization model (C-PCM) with switching/Gaussian smooth discretization is a widely used implicit solvation model in chemical simulations. However, its application in quantum mechanical calculations of large-scale biomolecular systems can be limited by computational expense of both the gas phase electronic structure and the solvation interaction. We have previously used graphical processing units (GPUs) […]
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I.A. Surmin, S.I. Bastrakov, E.S. Efimenko, A.A. Gonoskov, A.V. Korzhimanov, I.B. Meyerov
This paper concerns development of a high-performance implementation of the Particle-in-Cell method for plasma simulation on Intel Xeon Phi coprocessors. We discuss suitability of the method for Xeon Phi architecture and present our experience of porting and optimization of the existing parallel Particle-in-Cell code PICADOR. Direct porting with no code modification gives performance on Xeon […]
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Giuseppe Cerati, Peter Elmer, Steven Lantz, Kevin McDermott, Dan Riley, Matevz Tadel, Peter Wittich, Frank Wurthwein, Avi Yagil
Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors, but the future will be even more exciting. In order to stay within the power density limits but still obtain Moore’s Law performance/price gains, it will be necessary to parallelize algorithms to […]
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