Blesson Varghese
The risk of reinsurance portfolios covering globally occurring natural catastrophes, such as earthquakes and hurricanes, is quantified by employing simulations. These simulations are computationally intensive and require large amounts of data to be processed. The use of many-core hardware accelerators, such as the Intel Xeon Phi and the NVIDIA Graphics Processing Unit (GPU), are desirable […]
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Francisco Javier Ramírez-Gil, Marcos de Sales Guerra Tsuzuki, Wilfredo Montealegre-Rubio
The finite element method (FEM) has several computational steps to numerically solve a particular problem, to which many efforts have been directed to accelerate the solution stage of the linear system of equations. However, the finite element matrix construction, which is also time-consuming for unstructured meshes, has been less investigated. The generation of the global […]
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Moritz Kreutzer, Georg Hager, Gerhard Wellein, Andreas Pieper, Andreas Alvermann, Holger Fehske
The Kernel Polynomial Method (KPM) is a well-established scheme in quantum physics and quantum chemistry to determine the eigenvalue density and spectral properties of large sparse matrices. In this work we demonstrate the high optimization potential and feasibility of peta-scale heterogeneous CPU-GPU implementations of the KPM. At the node level we show that it is […]
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Blesson Varghese, Andrew Rau-Chaplin
Aggregate Risk Analysis is a computationally intensive and a data intensive problem, thereby making the application of high-performance computing techniques interesting. In this paper, the design and implementation of a parallel Aggregate Risk Analysis algorithm on multi-core CPU and many-core GPU platforms are explored. The efficient computation of key risk measures, including Probable Maximum Loss […]
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Aman Bahl, Oliver Baltzer, Andrew Rau-Chaplin, Blesson Varghese
At the heart of the analytical pipeline of a modern quantitative insurance/reinsurance company is a stochastic simulation technique for portfolio risk analysis and pricing process referred to as Aggregate Analysis. Support for the computation of risk measures including Probable Maximum Loss (PML) and the Tail Value at Risk (TVAR) for a variety of types of […]
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George Zaki
A variety of multiprocessor architectures has proliferated even for off-the-shelf computing platforms. To make use of these platforms, traditional implementation frameworks focus on implementing Digital Signal Processing (DSP) applications using special platform features to achieve high performance. However, due to the fast evolution of the underlying architectures, solution redevelopment is error prone and re-usability of […]
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Jamroz Michal, Kolinski Andrzej
BACKGROUND: The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the […]
Teruyoshi Washizawa, Yasuhiro Nakahara
We investigate applicability of GPU to DEM. NVIDIA’s code obtained superior performance than CPU in computational time. A model of contact forces in NVIDIA’s code is too simple for practical use. We modify this model by replacing it with the practical model. The simulation shows that the practical model obtains the computing speed 6 times […]
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Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira
Much of the current focus in high performance computing (HPC) for computational fluid dynamics (CFD) deals with grid based methods. However, parallel implementations for new meshfree particle methods such as Smoothed Particle Hydrodynamics (SPH) are less studied. In this work, we present optimizations for both central processing unit (CPU) and graphics processing unit (GPU) of […]
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J.C. Chedjou, K. Kyamakya, U.A. Khan, M.A. Latif
One of the most common approaches to avoid complexity while numerically solving stiff ordinary differential equations (ODEs) is approximating them by ignoring the nonlinear terms. While facing stiff partial differential equations (PDEs) the same is done by avoiding/suppressing the nonlinear terms from the Taylor’s series expansion. By so doing, the traditional methods for solving stiff […]
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Jean-Charles Tournier, Vaibhav Donde, Zhao Li
This paper investigates the potential of General Purpose Graphic Processing Unit (GPGPU) for the serve rand HMI parts of Energy Management System (EMS). TheHMI investigation focuses on the applicability and performance improvement of GPGPU for scattered data interpolation algorithms typically used to visually represent the overall state of a power network. The server side investigation […]
K. Morimoto, M. Inui
Large molds with very deep shape are well used in producing bumpers and inner panels of automobiles. In order to realize the precise and stable machining of such deep molds, 3-axis milling with inclined cutters are often applied. In this paper, we propose a new algorithm for determining the optimal cutting direction in such inclined […]
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