high performance computing on graphics processing units: hgpu.org

Computational fluid dynamics (CFD) methods have been employed in the studies of subjects such as aeroacoustics, gas dynamics, turbo machinery, viscoelastic fluids, among others. However, the need for accuracy and high performance resulted in methods whose solutions are becoming increasingly more complex. In this context, feature extraction and visualization methods play a key role, making […]

By exploring different granularities of data-level and task-level parallelism, we map 16 implementations of an Advanced Encryption Standard (AES) encipher with both online and offline key expansion on a fine-grained many-core system. The smallest design utilizes only 6 cores for offline key expansion and 8 cores for online key expansion, while the largest requires 107 […]

This paper describes one of ways to represent tree-like structures in Data Bases. Authors suggest to expand V. Tropashko nested intervals model. Numbers in intervals are described in system of residual classes. It allows to avoid storage of big numbers and easily implemented by parallel-programming algorithms.

As CPU clock frequencies plateau and the doubling of CPU cores per processor exacerbate the memory wall, hybrid core computing, utilizing CPUs augmented with FPGAs and/or GPUs holds the promise of addressing highperformance computing demands, particularly with respect to performance, power and productivity. This paper compares the sustained performance of a complex, single precision, floating-point, […]

BACKGROUND: Prediction of ribonucleic acid (RNA) secondary structure remains one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. Thus far, few studies have been reported on the acceleration of the Zuker algorithm on general-purpose processors or […]

Finite element methods (FEM) are most widely used for simulation of structural dynamics problems. Due to their highly compute intensive nature, these methods are used with domain decomposition where the problem is divided into subdomains which are individually solved and coupled together to obtain the final solution. One of the latest and most efficient approach […]

The recent rise in the popularity of Graphics Processing Units (GPUs) has been fueled by software frameworks, such as NVIDIA’s Compute Unified Device Architecture (CUDA) and Khronos Group’s OpenCL that make GPUs available for general purpose computing. However, CUDA and OpenCL are still lowlevel approaches that require users to handle details about data layout and […]

Occupancy grids are a very convenient tool for environment representation in robotics. This paper will detail a novel approach to compute occupancy grids from stereo-vision, and shows its application for the field of intelligent vehicles. In the proposed approach, occupancy is initially computed directly in the stereoscopic sensor’s disparity space. The calculation formally accounts for […]

The emergence and continuing use of multicore architectures with GPU accelerators require changes in the current software to address the gap between the accelerators’ computer vs the CPU-GPU communication speed. We describe how to develop linear algebra algorithms for these new and emerging hybrid architectures using XKaapi.

Knowledge extraction from structured data aims for identifying valid, novel, potentially useful, and ultimately understandable patterns in the data. The core step of this process is the application of a data mining algorithm in order to produce an enumeration of particular patterns and relationships in large databases. Clustering is one of the major data mining […]

This paper investigates the integration of feature extraction, object recognition and 3D reconstruction by stereo vision into a unified framework. In doing so, stereo vision can be made more robust by applying feature extraction results to the stereo matching process, and object recognition can be extended through the integration of depth information as another feature […]

This paper describes the use of GPU clusters to accelerate backpropagation for Synthetic Aperture Sonar (SAS) systems. We extended a GPU-based implementation of backpropagation to support clusters of GPU-enhanced nodes. The GPU accelerated implementation formed a 3,936 x 3,936 SAS image from 60s of sonar data in under 12s using a single GTX480, and under […]