high performance computing on graphics processing units: hgpu.org

In this paper, we analyze the power consumption of different GPU-accelerated iterative solver implementations enhanced with energy-saving techniques. Specifically, while conducting kernel calls on the graphics accelerator, we manually set the host system to a power-efficient idle-wait status so as to leverage dynamic voltage and frequency control. While the usage of iterative refinement combined with […]

In this paper a Grammar Guided Genetic Programming based method for the learning of rule-based classification systems is proposed. The method learns disjunctive normal form rules generated by means of a context-free grammar. The individual constitutes a rule based decision list that represents the full classifier. To overcome the problem of computational time of this […]

Energy efficiency is a major concern in modern high-performance-computing. Still, few studies provide a deep insight into the power consumption of scientific applications. Especially for algorithms running on hybrid platforms equipped with hardware accelerators, like graphics processors, a detailed energy analysis is essential to identify the most costly parts, and to evaluate possible improvement strategies. […]

From the standpoint of a computer engineer there are (at least) two ways to improve the execution time of an algorithm. First, one might build sequential processing units with increased speed (this is most common in CPUs, although those have also incorporated parallel processing paradigms), while the second alternative is to build a massive number […]

The topic of this thesis is ray tracing dynamic scenes and doing that efficiently while harnessing the massive computational power of today’s graphics cards. It is motivated by the ever increasing interest in raytracing and global illumination for creating effects in movies, but also the increased usage of 2D and 3D ray tracing in modern […]

Computation methods of parallel problem solving using graphic processing units (GPUs) have attracted much research interests in recent years. Parallel computation can be applied to genetic algorithms (GAs) in terms of the evaluation process of individuals in a population. This paper describes yet another implementation method of GAs to the CUDA environment where CUDA is […]

Digital mobile communication technologies, such as next generation mobile communication and mobile TV, are rapidly advancing. Hardware designs to provide baseband processing of new protocol standards are being actively attempted, because of concurrently emerging multiple standards and diverse needs on device functions, hardware-only implementation may have reached a limit. To overcome this challenge, digital communication […]

We present a novel solution to the problem of recovering and tracking the 3D position, orientation and full articulation of a human hand from markerless visual observations obtained by a Kinect sensor. We treat this as an optimization problem, seeking for the hand model parameters that minimize the discrepancy between the appearance and 3D structure […]

Continuum robots, with the capability of bending and extending at any point along their length mimic the abilities of an octopus arm or an elephant trunk. These manipulators present a number of exciting possibilities. While calculating a static solution for the system has been proven with certain models to produce satisfactory results [1], this approach […]

Nearest neighbor search is a core computational task in database systems and throughout data analysis. It is also a major computational bottleneck, and hence an enormous body of research has been devoted to data structures and algorithms for accelerating the task. Recent advances in graphics hardware provide tantalizing speedups on a variety of tasks and […]

Metagenomic sequence classification is a procedure to assign sequences to their source genomes. It is one of the important steps for metagenomic sequence data analysis. Although many methods exist, classification of high-throughput metagenomic sequence data in a limited time is still a challenge. We present here an ultra-fast metagenomic sequence classification system (MetaBinG) using graphic […]

We present a computational framework for multi-scale simulations of real-life biofluidic problems. The framework allows to simulate suspensions composed by hundreds of millions of bodies interacting with each other and with a surrounding fluid in complex geometries. We apply the methodology to the simulation of blood flow through the human coronary arteries with a spatial […]