Monte Carlo (MC) method is able to accurately calculate eigenvalues in reactor analysis. Its lengthy computation time can be reduced by general-purpose computing on Graphics Processing Units (GPU), one of the latest parallel computing techniques under development. The method of porting a regular transport code to GPU is usually very straightforward due to the “embarrassingly parallel” nature of...

The paper presents a method for performance improvements of a speech recognition system by moving a part of the computation acoustic likelihood computation onto a Graphics Processor Unit (GPU). In the system, GPU operates as a low cost powerful coprocessor for linear algebra operations. The paper compares GPU implementation of two techniques of acoustic likelihood computation: full Gaussian com...

1. Abstract This work presents the implementation of a topology optimization approach based on level set method in massively parallel computer architectures, in particular on a Graphics Processing Unit (GPU). Such architectures are becoming so popular during last years for complex and tedious scientific computation. They are composed of dozens, hundreds, or even thousands of cores specially des...

8 Abstract We have successfully ported an arbitrary high9 order discontinuous Galerkin method for solving the three10 dimensional isotropic elastic wave equation on unstruc11 tured tetrahedral meshes to multiple GPU using CUDA and 12 MPI and obtained a speedup factor of about 28.3 for the 13 single-precision version of our codes and a speedup factor 14 of about 14.9 for the double-precision ver...

Traffic noise mapping of cities requires large computer calculation times. This originates from the large number of point-to-point sound propagation calculations that must be performed. In this article it is demonstrated that noise mapping calculation times can be reduced considerably by the use of parallel computation on the Graphics Processing Unit (GPU) of a personal computer. Comparisons ar...

This contribution shows how unsupervised Markovian segmentation techniques can be accelerated when implemented on graphics hardware equipped with a Graphics Processing Unit (GPU). Our strategy exploits the intrinsic properties of local interactions between sites of a Markov Random Field model with the parallel computation ability of a GPU. This paper explains how classical iterative site-wise-u...

The advent of readily available temporal imaging or time series volumetric (4D) imaging has become an indispensable component of treatment planning and adaptive radiotherapy (ART) at many radiotherapy centers. Deformable image registration (DIR) is also used in other areas of medical imaging, including motion corrected image reconstruction. Due to long computation time, clinical applications of...

In this poster, we present how our previously published method of computing continuous 2D scatterplots can be performed with hardware acceleration on a GPU. By doing this, we exploit the parallel processing ability of current graphics hardware to improve the performance of continuous scatterplots by up to two orders of magnitude. For medium-sized tetrahedral data sets, we achieve interactive co...

Elliptic curve discrete logarithm problem (ECDLP) is one of the most important hard problems that modern cryptography, especially public key cryptography, relies on. And many efforts are dedicate to solve this problem. In recent days, GPU technology develops very fast and GPU has become a powerful tool for massive computation. In this paper, we give an implementation of parallel Pollard ρ metho...

In this article, a massively parallel approach of the multilevel fast multipole algorithm (PMLFMA) on graphics processing unit (GPU) heterogeneous platform, noted as GPU-PMLFMA, is presented for solving extremely large electromagnetic scattering problems involving tens billions unknowns, approach, flexible and efficient ternary partitioning scheme employed at first to partition MLFMA octree amo...