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Fumihiko Ino, Yosuke Oka, Kenichi Hagihara
The emergence of compute unified device architecture (CUDA), which has relieved application developers from having to understand complex graphics pipelines, has made the graphics processing unit (GPU) useful not only for graphics applications but also for general applications. In this paper, we present a cycle sharing system named GPU grid, which exploits idle GPU cycles […]
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Massimo Cafaro, Giovanni Aloisio (Eds.)
Provides a thorough introduction and overview of existing technologies in grids, clouds and virtualization, including a brief history of the field. Examines both business and scientific applications of grids and clouds. Presents contributions from an international selection of experts in the field. Research into grid computing has been driven by the need to solve large-scale, […]
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Marcus Hinders
This thesis describes how the performance of job management systems on heterogeneous computing grids can be increased with Graphics Processing Units (GPU). The focus lies on describing what is required to extend the grid to support the Open Computing Language (OpenCL) and how an OpenCL application can be implemented for the heterogeneous grid. Additionally, already […]
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Maraike Schellmann, Sergei Gorlatch, Dominik Meilander, Thomas Kosters, Klaus Schafers, Frank Wubbeling, Martin Burger
We present a variety of possible parallelization approaches for a real-world case study using several modern parallel and distributed computer architectures. Our case study is a production-quality, time-intensive algorithm for medical image reconstruction used in computer tomography. We describe how this algorithm can be parallelized for the main kinds of contemporary parallel architectures: shared-memory multiprocessors, […]
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Ingrid Scholl, Til Aach, Thomas M. Deserno, Torsten Kuhlen
In todays health care, imaging plays an important role throughout the entire clinical process from diagnostics and treatment planning to surgical procedures and follow up studies. Since most imaging modalities have gone directly digital, with continually increasing resolution, medical image processing has to face the challenges arising from large data volumes. In this paper, we […]
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S. Sirisup, S. U-raekolan, E. Kijsipongse
As technology advances, computing resources also gain benefits in many aspects: larger capacity, increased capability as well as rapidity. However, with heterogeneously distributed resources in Grid computing environment, the development an application to fully utilize the resources is a challenge. Especially, the computing resources themselves regularly upgrade their computing power for example by recruiting General […]
Flavio Vella, Riccardo M. Cefal, Alessandro Costantini, Osvaldo Gervasi, Claudio Tanci
Recently GPU computing, namely the possibility to use the vector processors of graphics card as computational general purpose units of High Performance Computing environments, has generated considerable interest in the scientific community. Some communities in European Grid Infrastructure (EGI) are reshaping their applications to exploit this new programming paradigm. Each EGI community, called Virtual Organization […]
Ke Liu, Jingli Zhou, Leihua Qin, Ning Lv
Cloud storage has been increasing in popularity recently due to its ability to deliver virtualized storage on demand over a network. As the amount of digital resources continues to grow at an astounding rate, more and more intelligent devices (such as GPU) are embedded as computing units to enhance the performance of storage system. How […]
Weimin Zheng, Bo Wang, Yongwei Wu
Parallel computing becomes more and more popular and the scale of software improves accordingly. A large application is made up of many small tasks. Some statistics indicate that some tasks of 80% software can support parallel execution. The difficulties are how to decompose one application into many tasks and exploit the parallelization among these tasks. […]
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee
In this paper, we present an efficient Hierarchical Parallel Genetic Algorithm framework using Grid computing (GE-HPGA). The framework is developed using standard Grid technologies, and has two distinctive features: (1) an extended GridRPC API to conceal the high complexity of the Grid environment, and (2) a metascheduler for seamless resource discovery and selection. To assess […]
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Fumihiko Ino, Akihiro Ogita, Kentaro Oita, Kenichi Hagihara
Exploiting the graphics processing unit (GPU) is useful to obtain higher performance with a less number of host machines in grid systems. One problem in GPU-accelerated grid systems is the lack of efficient multitasking mechanisms. In this paper, we propose a cooperative multitasking method capable of simultaneous execution of a graphics application and a CUDA-based […]
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Y. Kotani, F. Ino, K. Hagihara
This paper presents a resource selection system for exploiting graphics processing units (GPUs) as general-purpose computational resources in desktop Grid environments. Our system allows Grid users to share remote GPUs, which are traditionally dedicated to local users who directly see the display output. The key contribution of the paper is to develop this novel system […]
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