high performance computing on graphics processing units: hgpu.org

Algorithm-specific, i.e., semantic-specific optimizations have been observed to bring significant performance gains, especially for a diverse set of multi/many-core architectures. However, current programming models and compiler technologies for the state-of-the-art architectures do not exploit well these performance opportunities. In this paper, we propose a pattern-making methodology that enables algorithm-specific optimizations to be encapsulated into "optimization […]

This paper describes a local dimming method for reducing the power consumption of LCD monitors. Reducing this load is of ever growing importance as it is getting the dominant power consumer of mobile computing. As a side effect, our method does not only significantly reduce the power consumption but also improves the visual quality (see […]

Automatically parallelizing loop nests into CUDA kernels must exploit the full potential of GPUs to obtain high performance. One state-of-the-art approach makes use of the polyhedral model to extract parallelism from a loop nest by applying a sequence of affine transformations to the loop nest. However, how to automate this process to exploit both intraand […]

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 […]