1488

Posts

Nov, 9

ABC-SysBio–approximate Bayesian computation in Python with GPU support

Motivation: The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions. Results: Here […]
Nov, 9

DiVinE-CUDA – A Tool for GPU Accelerated LTL Model Checking

In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking. We demonstrate […]
Nov, 8

Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

In a recommendation system, customers’ preferences are encoded into vectors, and finding the nearest vectors to each vector is an essential part. We define this part of problem as a $k$-nearest vector problem and give an effective algorithm to solve it on multiple graphics processor units (GPUs). By an experiment, we show that when the […]
Nov, 8

Analysing Astronomy Algorithms for GPUs and Beyond

Astronomy depends on ever increasing computing power. Processor clock-rates have plateaued, and increased performance is now appearing in the form of additional processor cores on a single chip. This poses significant challenges to the astronomy software community. Graphics Processing Units (GPUs), now capable of general-purpose computation, exemplify both the difficult learning-curve and the significant speedups […]
Nov, 8

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel computational devices that can be housed in conventional desktop and laptop computers. For certain classes of Monte Carlo algorithms they offer massively parallel simulation, […]
Nov, 8

N-Body Simulations on GPUs

Commercial graphics processors (GPUs) have high compute capacity at very low cost, which makes them attractive for general purpose scientific computing. In this paper we show how graphics processors can be used for N-body simulations to obtain improvements in performance over current generation CPUs. We have developed a highly optimized algorithm for performing the O(N^2) […]
Nov, 8

Integrating Post-Newtonian Equations on Graphics Processing Units

We report on early results of a numerical and statistical study of binary black hole inspirals. The two black holes are evolved using post-Newtonian approximations starting with initially randomly distributed spin vectors. We characterize certain aspects of the distribution shortly before merger. In particular we note the uniform distribution of black hole spin vector dot […]
Nov, 8

Graphic-Card Cluster for Astrophysics (GraCCA) – Performance Tests

In this paper, we describe the architecture and performance of the GraCCA system, a Graphic-Card Cluster for Astrophysics simulations. It consists of 16 nodes, with each node equipped with 2 modern graphic cards, the NVIDIA GeForce 8800 GTX. This computing cluster provides a theoretical performance of 16.2 TFLOPS. To demonstrate its performance in astrophysics computation, […]
Nov, 8

Quantile Mechanics II: Changes of Variables in Monte Carlo methods and a GPU-Optimized Normal Quantile

This article presents differential equations and solution methods for the functions of the form $A(z) = F^-1(G(z))$, where $F$ and $G$ are cumulative distribution functions. Such functions allow the direct recycling of Monte Carlo samples from one distribution into samples from another. The method may be developed analytically for certain special cases, and illuminate the […]
Nov, 8

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

We use a graphics processing unit (GPU) for fast calculations of helicity amplitudes of quark and gluon scattering processes in massless QCD. New HEGET ( HELAS Evaluation with GPU Enhanced Technology) codes for gluon self-interactions are introduced, and a C++ program to convert the MadGraph generated FORTRAN codes into HEGET codes in CUDA (a C-platform […]
Nov, 8

GPUs for data processing in the MWA

The MWA is a next-generation radio interferometer under construction in remote Western Australia. The data rate from the correlator makes storing the raw data infeasible, so the data must be processed in real-time. The processing task is of order ~10 TFLOPS. The remote location of the MWA limits the power that can be allocated to […]
Nov, 8

Caracteristiques arithmetiques des processeurs graphiques

Les unites graphiques (Graphic Processing Units-GPU) sont desormais des processeurs puissants et flexibles. Les dernieres generations de GPU contiennent des unites programmables de traitement des sommets (vertex shader) et des pixels (pixel shader) supportant des operations en virgule flottante sur 8, 16 ou 32 bits. La representation flottante sur 32 bits correspond a la simple […]

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