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Michelle Perry
This dissertation studies a graphical processing unit (GPU) construction of Bayesian neural networks (BNNs) using large training data sets. The goal is to create a program for the mapping of phenomenological Minimal Supersymmetric Standard Model (pMSSM) parameters to their predictions. This would allow for a more robust method of studying the Minimal Supersymmetric Standard Model, […]
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M. P. Wachowiak, B. B. Sarlo, A. E. Lambe Foster
Much work has recently been reported in parallel GPU-based particle swarm optimization (PSO). Motivated by the encouraging results of these investigations, while also recognizing the limitations of GPU-based methods for big problems using a large amount of data, this paper explores the efficacy of employing other types of parallel hardware for PSO. Most commodity systems […]
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Evan E. Schneider, Brant E. Robertson
We present Cholla (Computational Hydrodynamics On ParaLLel Architectures), a new three-dimensional hydrodynamics code that harnesses the power of graphics processing units (GPUs) to accelerate astrophysical simulations. Cholla models the Euler equations on a static mesh using state-of-the-art techniques, including the unsplit Corner Transport Upwind (CTU) algorithm, a variety of exact and approximate Riemann solvers, and […]
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Matthew Thomas Calef, John Greaton Wohlbier
We describe the problem of iterating over mesh zones and iterating over material data within a zone, in the context of relatively new compute architectures. We present an example for how this can be done in a way that is portable across parallel programming environments and can be made to perform well. We offer a […]
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Eirik Myklebost
Finite-Difference Time-Domain (FDTD) is a popular technique for modeling computational electrodynamics, and is used within many research areas, such as the development of antennas, ultrasound imaging, and seismic wave propagation. Simulating large domains can however be very compute and memory demanding, which has motivated the use of cluster computing, and lately also the use of […]
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H. Wan Chan Tseung, J. Ma, C. Beltran
Purpose: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on GPUs. However, these usually use simplified models for non-elastic (NE) proton-nucleus interactions. Our primary goal is to build a GPU-based proton transport MC with detailed modeling of elastic and NE collisions. Methods: Using CUDA, we implemented GPU kernels for these […]
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Benjamin Brock, Andrew Belt, Jay Jay Billings, Mike Guidry
We demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve […]
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J. Spiechowicz, M. Kostur, L. Machura
This work presents an updated and extended guide on methods of a proper acceleration of the Monte Carlo integration of stochastic differential equations with the commonly available NVIDIA Graphics Processing Units using the CUDA programming environment. We outline the general aspects of the scientific computing on graphics cards and demonstrate them with two models of […]
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Makoto Sadahiro
By projecting observed microseismic data backward in time to when fracturing occurred, it is possible to locate the fracture events in space, assuming a correct velocity model. In order to achieve this task in near real-time, a robust computational system to handle backward propagation, or Reverse Time Migration (RTM), is required. We can then test […]
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Chen Shen, Xian-liang Wu
In recent years, the finite difference time domain (FDTD) method has been prevailed in the simulation of metamaterials widely. As the FDTD method can be suitable for the parallel computing, we apply this method to the Fermi-architecture Graphic Process Units (GPUs) to calculate the electromagnetic simulation of double negative materials in this paper. Finally, both […]
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O. Kaczmarek, C. Schmidt, P. Steinbrecher, Swagato Mukherjee, M. Wagner
The runtime of a Lattice QCD simulation is dominated by a small kernel, which calculates the product of a vector by a sparse matrix known as the "Dslash" operator. Therefore, this kernel is frequently optimized for various HPC architectures. In this contribution we compare the performance of the Intel Xeon Phi to current Kepler-based NVIDIA […]
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Wonhak Son
The technology of computational devices has been developed over several decades especially graphic processors which not only deal with graphic works but also compute scientific problems. This processor is suitable for parallel computations instead of using expensive high-end devices. Many research groups have implemented parallel computations using the MPI method with multi CPUs to solve […]
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