high performance computing on graphics processing units: hgpu.org

Atomistic molecular dynamics (MD) simulations are a vital tool in chemical research, as they are able to provide a view of chemical systems and processes that is not obtainable through experiment. However, large-scale MD simulations require access to multicore clusters or supercomputers that are not always available to all researchers. Recently, many have begun to […]

This paper presents a novel application of the GPU processing power to a very computationally demanding articulated human body tracking problem in a view-based approach. This work includes some optimizations at the algorithmic level as well as some tricks at the implementation level using OpenGL and shader programming. An underlying particle filter framework is combined […]

Energy minimization is an important step in molecular modeling, with applications in molecular docking and in mapping binding sites. Minimization involves repeated evaluation of various bonded and non-bonded energies of a protein complex. It is a computationally expensive process, with runtimes typically being many hours on a desktop system. In the current article, we present […]

In this paper, we compare the architectural perspectives of the Wave Field Synthesis (WFS) 3D-audio algorithm mapped on three different platforms: a General Purpose Processor (GPP), a Graphics Processor Unit (GPU) and a Field Programmable Gate Array (FPGA). Previous related work reveals that, up to now, WFS sound systems are based on standard PCs. However, […]

This paper studies the usage of the GPU as a collection of groups of related processing units, where each group communicates in some way to complete a computation efficiently and effectively. In particular, we use the GPU to perform jump flooding to pass information among groups of processing units in the design of two simple […]

IP address lookup is a challenging problem due to the increasing routing table size, and higher line rate. This paper investigates a new way to build an efficient IP lookup scheme using graphics processor units(GPU). Our contribution here is to design a basic architecture for high-performance IP lookup engine with GPU, and to develop efficient […]

SBART was developed in early 1990’s as one of the derivatives from Artificial Evolution by Karl Sims. It has a functionality to create a movie from a bred image through post-processing. The innovation of graphics processing unit (GPU) in these years improved the calculation performance to be fast enough to realize breeding animations in realtime […]

Exploiting the graphics processing unit (GPU) is useful to obtain higher performance with a less number of host machines in grid systems. One problem in GPU-accelerated grid systems is the lack of efficient multitasking mechanisms. In this paper, we propose a cooperative multitasking method capable of simultaneous execution of a graphics application and a CUDA-based […]

A new three-dimensional Navier-Stokes solver for flows in turbomachines has been developed. The new solver is based on the latest version of the Denton codes but has been implemented to run on graphics processing units (GPUs) instead of the traditional central processing unit. The change in processor enables an order-of-magnitude reduction in run-time due to […]

The use of graphics processing units (GPUs) in simulation applications offers a significant speed gain as compared to computations on central processing units (CPUs). Many simulation methods require a large number of independent random variables generated at each step. We present two approaches for implementation of random number generators (RNGs) on a GPU. In the […]

This paper is concerned with a multiresolution representation for maximum intensity projection (MIP) volume rendering based on morphological pyramids which allows progressive refinement. We consider two algorithms for progressive rendering from the morphological pyramid: one which projects detail coefficients level by level, and a second one, called streaming MIP, which resorts the detail coefficients of […]

Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic perspectives into brain function. Mining neuronal spike streams from these chips is critical to understand the firing patterns of neurons and gain insight into the underlying cellular activity. To address this need, we present a solution that uses a massively […]