high performance computing on graphics processing units: hgpu.org

Graphics Processing Units (GPUs) have become the focus of much interest with the scientific community lately due to their highly parallel computing capabilities, and cost effectiveness. They have evolved from simple graphic rendering devices to extremely complex parallel processors, used in a plethora of scientific areas. This paper outlines experimental results of a comparison between […]

Graphics processing units (GPUs) have the potential to greatly accelerate many applications, and yet programming models still remain too low level. Many language-based solutions to date have addressed this problem by creating embedded domain-specific languages that compile to CUDA or OpenCL. These targets are meant for human programmers and thus are less than ideal compilation […]

With the shift in high-performance computing (HPC) towards energy efficient hardware architectures such as accelerators (NVIDIA GPUs) and embedded systems (ARM processors), arose the need to adapt existing performance analysis tools to these new systems. We present EZTrace – a performance analysis framework for parallel applications. EZTrace relies on several core components, in particular on […]

Molecular Dynamics (MD) simulations provide a molecular-resolution picture of the folding and assembly processes of biomolecules, however, the size and timescales of MD simulations are limited by the computational demands of the underlying numerical algorithms. Recently, Graphics Processing Units(GPUs), specialized devices that were originally designed for rendering images, have been repurposed for high performance computing […]

Training of Artificial Neural Networks for large data sets is a time consuming task. Various approaches have been proposed to reduce the efforts, many of them by applying parallelization techniques. In this paper we develop and analyze two novel parallel training approaches for Backpropagation neural networks for face recognition. We focus on two specific parallelization […]

In this paper, we present a fast and scalable method for computing eigenvector centrality using graphics processing units (GPUs). The method is designed to compute the centrality on gene-expression networks, where the network is pre-constructed in the form of kNN graphs from DNA microarray data sets.

Building upon 28 years of history and the reputation for high quality papers, the ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (ACM SIGSIM PADS) is the flagship conference of ACM’s Special Interest Group on Simulation and Modeling (SIGSIM). ACM SIGSIM PADS focuses on the intersection of Computer Science and Modeling and Simulation (M&S). […]

We discuss the application of graphical processing units (GPUs) to accelerate real-space density functional theory (DFT) calculations. To make our implementation efficient, we have developed a scheme to expose the data parallelism available in the DFT approach; this is applied to the different procedures required for a real-space DFT calculation. We present results for current-generation […]

Graphics Processing Units (GPUs) have been shown to be effective at achieving large speedups over contemporary chip multiprocessors (CMPs) on massively parallel programs. The lack of well-defined GPU memory models, however, prevents support of high-level languages like C++ and Java, and negatively impacts their programmability. This thesis proposes to improve GPU programmability by adding support […]

Scatter correction is very important in 3D PET reconstruction due to a large scatter contribution in measurements. Currently, one of the most popular methods is so called single scatter simulation (SSS), which considers single Compton scattering contributions from many randomly distributed scatter points. The SSS enables a fast calculation of scattering with a relatively high […]

The computation of virtual acoustics for physical modelling synthesis using the finite difference time domain is a computationally expensive process, especially at audio rates such as 44.1kHz. However, the high level of dataindependence is well suited to parallel architectures such as those provided by graphics processing units. This paper describes the use of the latest […]

The BD-tree is an efficient database index structure which has good random access performance like hashing methods and can also provide range search and key sequential access like the B+-tree. In order to further improve the operational performance of the BD-tree, we adapted the traditional BD-tree hash function to realize the BD-tree parallel processing. By […]