high performance computing on graphics processing units: hgpu.org

Image segmentation is a very important step in many GIS applications. Mean shift is an advanced and versatile technique for clustering-based segmentation, and is favored in many cases because it is non-parametric. However, mean shift is very computationally intensive compared with other simple methods such as k-means. In this work, we present a hybrid design […]

Present need to move towards heterogeneous architectures has been well established. This has increased the importance of parallelization of software to achieve good performance. Use of mixed architectures exponentially increases the need of the programmer to understand the intricacies of the underlying hardware to achieve optimal speedup. Obtaining optimal performance on one such architecture is […]

In this paper an inverse preconditioner for the numerical solution of an elliptic Laplace prob- lem of a global circulation ocean model is presented. The inverse preconditiong technique is adopted in order to efficiently compute the numerical solution of the elliptic kernel by using the Conjugate Gradient (CG) method. We show how the performance and […]

The arrival of graphics processing (GPU) cards suitable for massively parallel computing promises affordable large-scale neural network simulation previously only available at supercomputing facilities. While the raw numbers suggest that GPUs may outperform CPUs by at least an order of magnitude, the challenge is to develop fine-grained parallel algorithms to fully exploit the particulars of […]

The Richardson-Lucy method is the most popular deconvolution method in astronomy because it preserves the number of counts and the non-negativity of the original object. Regularization is, in general, obtained by an early stopping of Richardson-Lucy iterations. In the case of point-wise objects such as binaries or open star clusters, iterations can be pushed to […]

Content reuse is extremely common in user generated mediums. Reuse detection serves as be the basis for many applications. However, along with the explosion of Internet and continuously growing uses of user generated mediums, the task becomes more critical and difficult. In this paper, we present a novel efficient and scalable approach to detect content […]

In this paper, we present a novel method to couple Smoothed Particle Hydrodynamics (SPH) and nonlinear FEM to animate the interaction of fluids and deformable solids in real time. To accurately model the coupling, we generate proxy particles over the boundary of deformable solids to facilitate the interaction with fluid particles, and develop an efficient […]

In order to achieve greater amounts of computation while lowering the cost of artistic and scientific projects that rely on realtime digital signal processing techniques, it is interesting to study the performance of commodity parallel processing GPU cards coupled with commonly used software for realtime DSP. In this article, we describe the measurement of data […]

Network Intrusion Detection System (NIDS) analyzes network traffic for malicious activities and report’s findings from events that intend to compromise the security of the computers and other equipment. NIDS looks into both headers and payloads of the network packets to identify possible intrusions. NIDS models that only use Central Processing Units (CPU) such as the […]

In the advent of new large galaxy surveys, which will produce enormous datasets with hundreds of millions of objects, new computational techniques are necessary in order to extract from them any two-point statistic, the computational time of which grows with the square of the number of objects to be correlated. Fortunately technology now provides multiple […]

The optimization of the irregular connection network of the multiprocessor systems with the distributed memory is the NP complete problem which is generally compute-intensive process. Graphics processing units provide a large computational power at a very low price allowing the fine-grained parallelism. This work investigates the use of the GPU in the parallelisation of the […]

This paper presents a design for parallel processing of synthetic aperture radar (SAR) data using multiple Graphics Processing Units (GPUs). Our approach supports real-time reconstruction of a two-dimensional image from a matrix of echo pulses and their response values. Key to runtime efficiency is a partitioning scheme that divides the output image into tiles and […]