high performance computing on graphics processing units: hgpu.org

We show how the computational power and programmability of modern graphics processing units (GPUs) can be used to efficiently solve large-scale pixel-based material distribution problems using a gradient-based optimality criterion method. To illustrate the principle, a so-called topology optimization problem that results in a constrained nonlinear programming problem with over 4 million decision variables is […]

Elliptic-curve cryptography is becoming the standard public-key primitive not only for mobile devices but also for high-security applications. Advantages are the higher cryptographic strength per bit in comparison with RSA and the higher speed in implementations. To improve understanding of the exact strength of the elliptic-curve discrete-logarithm problem, Certicom has published a series of challenges. […]

We present an efficient implementation of a high performance parallel framework for Agent Based Modelling (ABM), exploiting the parallel architecture of the Graphics Processing Unit (GPU). It provides a mapping between formal agent specifications, with C based scripting, and optimised NVIDIA Compute Unified Device Architecture (CUDA) code. The mapping of agent data structures and agent […]

The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free parameters. We consider two well-known unsupervised learning models, deep belief networks (DBNs) and sparse coding, that have recently been applied to a flurry of machine learning applications (Hinton […]

We demonstrate the use of graphical processing units (GPUs) to carry out complete self-consistent-field calculations for molecules with as many as 453 atoms (2131 basis functions). Speedups ranging from 28? to 650? are achieved as compared to a mature third-party quantum chemistry program (GAMESS) running on a traditional CPU. The computational organization used to construct […]

During the last few years, GPUs have evolved from simple devices for the display signal preparation into powerful coprocessors that do not only support typical computer graphics tasks but can also be used for general numeric and symbolic computation tasks. As major advantage GPUs provide extremely high parallelism combined with a high bandwidth in memory […]

On the basis of studying Non-Local Means (NLM) denoising algorithm and its pixel-wise processing algorithm in Graphics Processing Unit (GPU), a whole image accumulation algorithm of NLM denoising algorithm based on GPU is proposed. The number of dynamic instructions of fragment shader is effectively reduced by redesigning the data structure and processing flow, that make […]

Latent Semantic Analysis (LSA) can be used to reduce the dimensions of large Term-Document datasets using Singular Value Decomposition. However, with the ever expanding size of data sets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. The Graphics Processing Unit (GPU) can solve some highly parallel […]

Direct numerical simulation (DNS) of turbulence is computationally intensive and typically relies on some form of parallel processing. Spectral kernels used for spatial discretization are a common computational bottleneck on distributed memory architectures. One way to increase DNS algorithms’ efficiency is to parallelize spectral kernels using tightly coupled single-program, multiple-data (SPMD) multiprocessor units with minimal […]

Web search engines are facing formidable performance challenges due to data sizes and query loads. The major engines have to process tens of thousands of queries per second over tens of billions of documents. To deal with this heavy workload, such engines employ massively parallel systems consisting of thousands of machines. The significant cost of […]

Progressive alignment is a widely used approach for computing multiple sequence alignments (MSAs). However, aligning several hundred or thousand sequences with popular progressive alignment tools such as ClustalW requires hours or even days on state-of-the-art workstations. This paper presents MSA-CUDA, a parallel MSA program, which parallelizes all three stages of the ClustalW processing pipeline using […]

Recently, general-purpose computation on graphics processing units (GPGPU) has become an increasingly popular field of study as graphics processing units (GPUs) continue to be proposed as high performance and relatively low cost implementation platforms for scientific computing applications. Among these applications figure astrophysical N-bodysimulations, which form one of the most challenging problems in computational science. […]