high performance computing on graphics processing units: hgpu.org

We present a three-dimensional finite difference time domain (FDTD) method on graphics processing unit (GPU) for plasmonics applications. For the simulation of plasmonics devices, the Lorentz-Drude (LD) dispersive model is incorporated into Maxwell equations, while the auxiliary differential equation (ADE) technique is applied to the LD model. Our numerical experiments based on typical domain sizes […]

Exploration of the time-domain radio sky has huge potential for advancing our knowledge of the dynamic universe. Past surveys have discovered large numbers of pulsars, rotating radio transients and other transient radio phenomena; however, they have typically relied upon off-line processing to cope with the high data and processing rate. This paradigm rules out the […]

This paper presents a programming language interface, a complete scripting language, to describe composable compiler transformations. These transformation programs can be written, shared and reused by non-expert application and library developers. From a compiler writer’s perspective, a scripting language interface permits rapid prototyping of compiler algorithms that can mix levels and compose different sequences of […]

Parabolic partial differential equations are often used to model systems involving heat transfer, acoustics, and electrostatics. The need for more complex models with increasing precision drives greater computational demands from processors. Since solving these types of equations is inherently parallel, GPU computing offers an attractive solution for drastically decreasing time to completion, power usage, and […]

The computational demands of multivariate clustering grow rapidly, and therefore processing large data sets, like those found in flow cytometry data, is very time consuming on a single CPU. Fortunately these techniques lend themselves naturally to large scale parallel processing. To address the computational demands, graphics processing units, specifically NVIDIA’s CUDA framework and Tesla architecture, […]

In this study, chaotic partial differential equations (PDEs) were numerically solved using a parallel algorithm on graphics processing units (GPU). This new method will aid in our search for simple examples of chaotic PDEs. Computational time using the GPU was compared to other languages such as Matlab and PowerBASIC. The GPU algorithm was optimized using […]

This paper explores effective algorithms for the solution of numerical nonlinear optimization problems in image restoration. The technology of modern acquisition techniques and devices most often returns data of increasing size, so we focus on the Scaled Gradient Projection algorithm, which is well suited to large-scale applications. We present its parallel implementations on different hardware, […]

In the past few years, the graphics processing units (GPU) has become trend in high performance computing (HPC). The newest Top500 list was showed three supercomputers contain GPU accelerator on Top10 in Nov. 2010. The role of the GPU accelerator has become more and more important for scientific computing and computational fluid dynamic (CFD) to […]

This is a feasibility study of using a modern Graphics Processing Unit (GPU) to parallelize the accelerator particle tracking code. To demonstrate the massive parallelization features provided by GPU computing, a simplified TracyGPU program is developed for dynamic aperture calculation. Performances, issues, and challenges from introducing GPU are also discussed.

This paper proposes a novel approach to optimally solve volumetric registration problems. The proposed framework exploits parametric dictionaries for sparse volumetric representations, l1 dissimilarities and DC (Difference of Convex functions) decomposition. The SAD (sum of absolute differences) criterion is applied to the sparse representation of the reference volume and a DC decomposition of this criterion […]

In the last few years a myriad of computer graphic applications have been developed using standard programming techniques, which are mainly based on multicore general-purpose processors (CPUs) architectures. Due to the rapid turning towards high definition multimedia, more and more researches have been done that need both computational resources and memory space to achieve high […]

We study the performance of a nonparaxial beam propagation method accelerated using massively parallel computation in graphic processing units. The implementation is tested in two different NVIDIA hardware architectures, Tesla and Fermi, and the results are compared with a CPU-based parallel implementation using Open MPI.