Andrew Kerr
Trends in computer engineering place renewed emphasis on increasing parallelism and heterogeneity. The rise of parallelism adds an additional dimension to the challenge of portability, as different processors support different notions of parallelism, whether vector parallelism executing in a few threads on multicore CPUs or large-scale thread hierarchies on GPUs. Thus, software experiences obstacles to […]
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Jose Unpingco, Juan Carlos Chaves
Recent trends in hardware development have led to graphics processing units (GPUs) evolving into highly-parallel, multi-core computing platforms suitable for computational science applications. Recently, GPUs such as the NVIDIA Tesla 20-series (with up to 448 cores) have become available to the High Performance Computing Modernization Program (HPCMP) user community. Traditionally, NVIDIA GPUs are programmed using […]
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James Laurence Brock
Homogeneous multicore processors, heterogeneous multicore processors, high performance accelerators, and other heterogeneous architectures have significant computing potential over traditional single core processors. Computer systems comprised of these specialized processing elements are increasingly common. Due to the increased complexity of these architectures, programming for them has become increasingly complex and error prone. Each of these architectures […]
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Luca Caucci
This dissertation investigates the application of list-mode data to detection, estimation, and image reconstruction problems, with an emphasis on emission tomography in medical imaging. We begin by introducing a theoretical framework for list-mode data and we use it to define two observers that operate on list-mode data. These observers are applied to the problem of […]
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M. G. Sanchez, V. Vidal, J. Bataller, G. Verdu
In this paper, we present an efficient implementation of parallel algorithms to remove noise in digital images using different Graphics Processing Units (GPUs). The algorithm, based on the concept of peer group, uses a fuzzy metric for finding wrong pixels and the Arithmetic Mean Filter (AMF) to correct it. There are many factors to study […]
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Juan Gomez-Luna, Jose Maria Gonzalez-Linares, Jose Ignacio Benavides, Nicolas Guil
Graphics Processing Units (GPU) have impressively arisen as generalpurpose coprocessors in high performance computing applications, since the launch of the Compute Unified Device Architecture (CUDA). However, they present an inherent performance bottleneck in the fact that communication between two separate address spaces (the main memory of the CPU and the memory of the GPU) is […]
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Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan
Many-core GPUs provide high computing ability and substantial bandwidth; however, optimizing irregular applications like SpMV on GPUs becomes a difficult but meaningful task. In this paper, we propose a novel method to improve the performance of SpMV on GPUs. A new storage format called HYB-R is proposed to exploit GPU architecture more efficiently. The COO […]
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P. Anders, H. Baumgardt, E. Gaburov, S. Portegies Zwart
Most recent progress in understanding the dynamical evolution of star clusters relies on direct N-body simulations. Owing to the computational demands, and the desire to model more complex and more massive star clusters, hardware calculational accelerators, such as GRAPE special-purpose hardware or, more recently, GPUs (i.e. graphics cards), are generally utilised. In addition, simulations can […]
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Jose Duato, Antonio J. Pena, Federico Silla, Juan C. Fernandez, Rafael Mayo, Enrique S. Quintana-Orti
In this paper we propose a first step towards a general and open source approach for using GPGPU (General-Purpose Computation on GPUs) features within virtual machines (VMs). In particular, we describe the use of rCUDA, a GPGPU virtualization framework, to permit the execution of GPU-accelerated applications within VMs, thus enabling GPGPU capabilities on any virtualized […]
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Sergio Sanchez, Abel Paz, Gabriel Martin, Antonio Plaza
Hyperspectral imaging instruments are capable of collecting hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. One of the main problems in the analysis of hyperspectral data cubes is the presence of mixed pixels, which arise when the spatial resolution of the sensor is not enough […]
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Janusz Bedkowski, Andrzej Maslowski
The main problem of the following paper is control and supervision of web connected mobile robots. Taking up this subject is justified by the need of developing new methods for control, supervision and integration of exis-ting modules (inspection robots, autonomous robots, mo-bile base station). The methodology consists of: multi ro-botic system structure, cognitive model of […]
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Alexandru Pirjan
Considering the importance and usefulness of real time data mining, in recent years the concern of researchers to discover new hardware architectures that can manage and process large volumes of data has increased significantly. In this paper the performance of algorithms for temporal data mining that are implemented in the new Compute Unified Device Architecture […]
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