high performance computing on graphics processing units: hgpu.org

Lattice spin models are useful for studying critical phenomena and allow the extraction of equilibrium and dynamical properties. Simulations of such systems are usually based on Monte Carlo (MC) techniques, and the main difficulty is often the large computational effort needed when approaching critical points. In this work, it is shown how such simulations can […]

MOTIVATION: Mathematical modelling is central to systems and synthetic biology. Using simulations to calculate statistics or to explore parameter space is a common means for analysing these models and can be computationally intensive. However, in many cases, the simulations are easily parallelizable. Graphics processing units (GPUs) are capable of efficiently running highly parallel programs and […]

The cardiac bidomain model is a popular approach to study electrical behavior of tissues and simulate interactions between the cells by solving partial differential equations. The iterative and data parallel model is an ideal match for the parallel architecture of Graphic Processing Units (GPUs). In this study, we evaluate the effectiveness of architecture-specific optimizations and […]

We present the results of a hierarchical N-body simulation on DEGIMA, a cluster of PCs with 576 graphic processing units (GPUs) and using an InfiniBand interconnect. DEGIMA stands for DEstination for GPU Intensive MAchine, and is located at Nagasaki Advanced Computing Center (NACC), Nagasaki University. In this work, we have upgraded DEGIMA_s interconnect using InfiniBand. […]

Structural parameters are normally extracted from observed galaxies by fitting analytic light profiles to the observations. Obtaining accurate fits to high-resolution images is a computationally expensive task, requiring many model evaluations and convolutions with the imaging point spread function. While these algorithms contain high degrees of parallelism, current implementations do not exploit this property. With […]

We present a flexible and highly efficient hardware-assisted volume renderer grounded on the original Projected Tetrahedra (PT) algorithm. Unlike recent similar approaches, our method is exclusively based on the rasterization of simple geometric primitives and takes full advantage of graphics hardware. Both vertex and geometry shaders are used to compute the tetrahedral projection, while the […]

SSL/TLS is a standard protocol for secure Internet communication. Despite its great success, today’s SSL deployment is largely limited to security-critical domains. The low adoption rate of SSL is mainly due to high computation overhead on the server side. In this paper, we propose Graphics Processing Units (GPUs) as a new source of computing power […]

Digital Particle Image Velocimetry (PIV) is an optical technique used to measure the velocity of seeded particles in real flow. A CCD camera captures the flow field twice under exposure to a short duration laser flash. Recorded image pairs are cross-correlated to extract velocity information from these records. Time resolved PIV technology can capture images […]

This paper compares three common evolutionary algorithms and our modified GA, a Distributed Adaptive Genetic Algorithm (DAGA). The optimal approach is sought to adapt, in near real-time, biological model behaviour to that of real biology within a laboratory. Near real-time adaptation is achieved with a Graphics Processing Unit (GPU). This, together with evolutionary computation, enables […]

If the computational demands of an interactive graphics rendering application cannot be met by a single commodity Graphics Processing Unit (GPU), multiple graphics accelerators may be utilised on multi-GPU based systems such as SLI [1] or Crossfire [2] or by a cluster of PCs in conjunction with a software infrastructure. Typically these PC cluster solutions […]

We present an efficient method for mutual information (MI) computation between images (2D or 3D) for NVIDIA’s “compute unified device architecture” (CUDA) compatible devices. Efficient parallelization of MI is particularly challenging on a “graphics processor unit” (GPU) due to the need for histogram-based calculation of joint and marginal probability mass functions (pmfs) with large number […]

Direct volume rendering of large volumetric data sets on programmable graphics hardware is often limited by the amount of available graphics memory and the bandwidth from main memory to graphics memory. Therefore, several approaches to volume rendering from compact representations of volumetric data have been published that avoid most of the data transfer between main […]