high performance computing on graphics processing units: hgpu.org

In adaptive radiotherapy, a deformable image registration is often conducted between the planning CT and the treatment CT (or cone beam CT) to generate a deformation vector field (DVF) for dose accumulation and contour propagation. The auto-propagated contours on the treatment CT may contain relatively large errors especially in low-contrast regions. Clinician’s inspection and editing […]

We discuss how the steepest descent method with Fourier acceleration for Laudau gauge fixing in lattice SU(3) simulations can be implemented using CUDA. The scaling of the gauge fixing code was investigated using a Tesla C2070 Fermi architecture, and compared with a parallel CPU gauge fixing code.

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, […]

Distance-to-Default(DTD), which is used to describe the default risk of a rm, acts an important role in credit research. Nowadays, since we can access a large amount of historical data, we can get a more accurate DTD result. However, this directly increases the computation time as well as the computation power. Meanwhile, Graphic Processing Unit(GPU), […]

PATRIC is a particle tracking code used at GSI to study collective effects in the FAIR synchrotrons. Due to the need for calculation-intense simulations, parallel programming methods are being explored to optimize calculation performance. Presently the tracking part of the code is parallelized using MPI, where each node represents one slice of the particles that […]

The application of General Purpose computing on a GPU is an effective way to accelerate the FDTD method. This work explores the different domain decomposition techniques from the literature and extends the theoretically best approach with additional flexibility. We examine the performance on both Tesla and Fermi architecture GPUs and identify the best way to […]

Matrix formalism is a map integration method for ODE solving. It allows to present solution of the system as sums and multiplications of 2-indexes numeric matrix. This approach can be easy implement in parallel codes. As the most natural for matrix operation GPU architecture has been chosen. The set of the methods for beam dynamics […]

Graphics Processing Units (GPUs) are workhorses of modern performance due to their ability to achieve massive speedups on parallel applications. The massive number of threads that can be run concurrently on these systems allow applications which have data-parallel computations to achieve better performance when compared to traditional CPU systems. However, the GPU is not perfect […]

A large number of Fortran legacy programs are still running in production environments, and most of these applications are running sequentially. Multi- and Many- core architectures are established as (almost) the only processing hardware available, and new programming techniques that take advantage of these architectures are necessary. In this report, we will explore the impact […]

Segmentation of CT-Angiography datasets is an important and difficult task. Several algorithms and approaches have already been invented and implemented to solve this problem. In this work, we present automatic algorithms for the segmentation of these CTA datasets, implemented in CUDA, and evaluate our results regarding speed and error rates. Starting with local approaches like […]

In recent years, there has been a drive towards parallel architectures to further increase computational performance. The many-core architecture of modern Graphics Processing Units (GPU) can be used for general computations in addition to graphics processing, and provide good performance for data parallel computations. In this thesis, we explore the processing powers of two generations […]

A silhouette gives an outline of a person or an object. When extracting silhouettes from an image or video, we acquire information about where in the image the foreground objects are located, their sizes and their shapes. This silhouette information can be useful in many ways. In computer vision, silhouette extraction plays an important role. […]