high performance computing on graphics processing units: hgpu.org

In this paper, we introduce several new schemes for calculation of discrete wavelet transforms of images. These schemes reduce the number of steps and, as a consequence, allow to reduce the number of synchronizations on parallel architectures. As an additional useful property, the proposed schemes can reduce also the number of arithmetic operations. The schemes […]

In recent years, Convolutional Neural Network (CNN) based methods have achieved great success in a large number of applications and have been among the most powerful and widely used techniques in computer vision. However, CNN-based methods are computational-intensive and resource-consuming, and thus are hard to be integrated into embedded systems such as smart phones, smart […]

Due to the proliferation of mobile devices and cloud computing, remote simulation and visualization have become increasingly important. In order to reduce bandwidth and (de)serialization costs, and to improve mobile battery life, we examine the performance and bandwidth benefits of using an optimizing query compiler for remote postprocessing of interactive and in-situ simulations. We conduct […]

We present a new tool for training neural network language models (NNLMs), scoring sentences, and generating text. The tool has been written using Python library Theano, which allows researcher to easily extend it and tune any aspect of the training process. Regardless of the flexibility, Theano is able to generate extremely fast native code that […]

Co-expression network is a critical technique for the identification of inter-gene interactions, which usually relies on all-pairs correlation (or similar measure) computation between gene expression profiles across multiple samples. Pearson’s correlation coefficient (PCC) is one widely used technique for gene co-expression network construction. However, all-pairs PCC computation is computationally demanding for large numbers of gene […]

Sponsors sponsored by Limerick Institute of Technology, University of Limerick (UL), Mary Immaculate College (MIC) and Irish Technology Leadership Group (ITLG). Conference Chair Prof. Seppo J. Sirkemaa, University of Turku, Finland Local Organising Co-chair Jerald Cavanagh, Limerick Institute of Technology, Ireland Padraig Kirby, Limerick Institute of Technology, Ireland Paper Publication Paper accepted by ICOAI 2016 […]

Topics of interest for submission include, but are not limited to: Advanced Intelligent Systems; Ant Colony Optimization and Swarm Intelligence; Artificial Immune Systems; Artificial Intelligence; Artificial Life; Associative Memory; Automatic Annotation; Bioinformatics and Biological Computing; Case-Based and Temporal Reasoning;   Conference Schedule November 23, 2016: Registration and Collecting conference materials November 24, 2016: Keynote speeches […]

This interdisciplinary workshop is organized to explore the scientific issues, challenges, and opportunities for supercomputing beyond the scaling limits of Moore’s Law, with the ultimate goal of keeping supercomputing at the forefront of computing technologies beyond the physical and conceptual limits of current systems. Continuing progress of supercomputing beyond the scaling limits of Moore’s Law […]

Publication International Journal of Modeling and Optimization (ISSN: 2010-3697) Indexed by Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, DOAJ, Google Scholar, EI (INSPEC, IET). Conference Schedule 1) July 22, 2016—Conference Materials Collection 2) July 23, 2016—Keynote Speeches & Oral Presentations 3) July 24, 2016—One-day tour in Beijing Conference Chairs Prof. Dr. Chen-Huei […]

Call for paper download: PDF The 2nd International Conference on Control Science and Systems Engineering (CCSSE 2016) will be held at Singapore, during July 27-29. Control Science and Systems Engineering are entering the second golden phase. These new challenges bring with it new research questions resulting in the need to stimulate the rapid awareness of […]

The hyperbolic Radon transform is a commonly used tool in seismic processing, for instance in seismic velocity analysis, data interpolation and for multiple removal. A direct implementation by summation of traces with different moveouts is computationally expensive for large data sets. In this paper we present a new method for fast computation of the hyperbolic […]

Deep learning framework supported by CUDA parallel computing platform boosts advances of studies on machine learning. The advantage of parallel processing largely comes from an efficiency of matrix-matrix multiplication using many CUDA-enabled graphics processing units (GPU). Therefore, for recurrent neural networks (RNNs), the usage of a zero-filled matrix representing variable lengths of sentences for a […]