S. Rit, M. Vila Oliva, S. Brousmiche, R. Labarbe, D. Sarrut, G. C. Sharp
We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in […]
Andrew L. Beam, Alison Motsinger-Reif, Jon Doyle
Discovering causal genetic variants from large genetic association studies poses many difficult challenges. Assessing which genetic markers are involved in determining trait status is a computationally demanding task, especially in the presence of gene-gene interactions. A non-parametric Bayesian approach in the form of a Bayesian neural network is proposed for use in analyzing genetic association […]
Aditya Deshpande, P J Narayanan
In this paper, we present an all-core implementation of Burrows Wheeler Compression algorithm that exploits all computing resources on a system. Our focus is to provide significant benefit to everyday users on common end-to-end applications by exploiting the parallelism of multiple CPU cores and many-core GPU on their machines. The all-core framework is suitable for […]
Jianbin Fang, Henk Sips, Lilun Zhang, Chuanfu Xu, Yonggang Che, Ana Lucia Varbanescu
Based on Intel’s Many Integrated Core (MIC) architecture, Intel Xeon Phi is one of the few truly many-core CPUs – featuring around 60 fairly powerful cores, two levels of caches, and graphic memory, all interconnected by a very fast ring. Given its promised ease-of-use and high performance, we took Xeon Phi out for a test […]
Axel Huebl, David Pugmire, Felix Schmitt, Richard Pausch, Michael Bussmann
Emerging new technologies in plasma simulations allow tracking billions of particles while computing their radiative spectra. We present a visualization of the relativistic Kelvin-Helmholtz Instability from a simulation performed with the fully relativistic particle-in-cell code PIConGPU powered by 18,000 GPUs on the USA’s fastest supercomputer Titan [1].
Simon L. Grimm, Joachim G. Stadel
We describe a GPU implementation of a hybrid symplectic N-body integrator, GENGA (Gravitational ENcounters with Gpu Acceleration), designed to integrate planet and planetesimal dynamics in the late stage of planet formation and stability analysis of planetary systems. GENGA is based on the integration scheme of the Mercury code (Chambers 1999), which handles close encounters with […]
Stephen Tyree, Jacob R. Gardner, Kilian Q. Weinberger, Kunal Agrawal, John Tran
In this paper, we evaluate the performance of various parallel optimization methods for Kernel Support Vector Machines on multicore CPUs and GPUs. In particular, we provide the first comparison of algorithms with explicit and implicit parallelization. Most existing parallel implementations for multi-core or GPU architectures are based on explicit parallelization of Sequential Minimal Optimization (SMO) […]
Gabor Janos Tornai, Gyorgy Cserey
In this paper, we investigated the effect of adding more small curves to the initial condition which determines the required number of iterations of a fast level set (LS) evolution. As a result, we discovered two new theorems and developed a proof on the worst case of the required number of iterations. Furthermore, we found […]
Stefan Lemvig Glimberg, Allan Peter Engsig-Karup, Allan S. Nielsen, Bernd Dammann
Massively parallel processors, such as graphical processing units (GPUs), have in recent years proven to be effective for a vast amount of scientific appli- cations. Today, most desktop computers are equipped with one or more pow- erful GPUs, offering heterogeneous high-performance computing to a broad range of scientific researchers and software developers. Though GPUs are […]
W. B. Langdon, M. Harman
Genetic Programming (GP) may dramatically increase the performance of software written by domain experts. GP and autotuning are used to optimise and refactor legacy GPGPU C code for modern parallel graphics hardware and software. Speed ups of more than six times on recent nVidia GPU cards are reported compared to the original kernel on the […]
Johannes Koster, Sven Rahmann
We present PEANUT (ParallEl AligNment UTility), a highly parallel GPU-based read mapper with several distinguishing features, including a novel q-gram index (called the q-group index) with small memory footprint built on-the-fly over the reads and the possibility to output both the best hits or all hits of a read. Designing the algorithm particularly for the […]
Ryan R. Newton, Eric Holk, Trevor L. McDonell
High-level domain-specific-languages for array processing on the GPU are increasingly common, but to date they run only on a single GPU. We argue that languages will need to target multiple devices, even simultaneous combinations of GPU/GPU and CPU/GPU. Increased flexibility may be key to making these languages more easily deployable and thus widespread. To this […]
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Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

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  • RAM: 12GB
  • OS: OpenSUSE 11.4
  • SDK: AMD APP SDK 2.8
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  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 5.0.35, AMD APP SDK 2.8

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