high performance computing on graphics processing units: hgpu.org

The numerical solution of the Vlasov-Fokker-Planck equation is a well established method to simulate the dynamics, including the self-interaction with its own wake field, of an electron bunch in a storage ring. In this paper we present Inovesa, a modularly extensible program that uses OpenCL to massively parallelize the computation. It allows a standard desktop […]

Many research works have recently experimented with GPU to accelerate packet processing in network applications. Most works have shown that GPU brings a significant performance boost when it is compared to the CPU-only approach, thanks to its highly-parallel computation capacity and large memory bandwidth. However, a recent work argues that for many applications, the key […]

OpenACC has been touted as a "high productivity" API designed to make GPGPU programming accessible to scientific programmers, but to date, no studies have attempted to verify this quantitatively. In this paper, we conduct an empirical investigation of program productivity comparisons between OpenACC and CUDA in the programming time, the execution time and the analysis […]

Current Deep Learning approaches have been very successful using convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers. Three limitations of this approach are: 1) they are based on a simple layered network topology, i.e., highly connected layers, without intra-layer connections; 2) the networks are manually configured to achieve optimal results, and […]

The solution of Protein-Ligand Docking Problems can be approached through metaheuristics, and satisfactory metaheuristics can be obtained with hyperheuristics searching in the space of metaheuristics implemented inside a parameterized schema. These hyperheuristics apply several metaheuristics, resulting in high computational costs. To reduce execution times, a shared-memory schema of hyperheuristics is used with four levels of […]

High-performance computing systems are more and more often based on accelerators. Computing applications targeting those systems often follow a host-driven approach in which hosts offload almost all compute-intensive sections of the code onto accelerators; this approach only marginally exploits the computational resources available on the host CPUs, limiting performance and energy efficiency. The obvious step […]

This report provides an introduction to some Machine Learning tools within the most common development environments. It mainly focuses on practical problems, skipping any theoretical introduction. It is oriented to both students trying to approach Machine Learning and experts looking for new frameworks.

Paper Publication All accepted papers must be written in English and will be published into #International Conference Proceedings Series by ACM, and indexed by Ei Compendex and Scopus. Proceedings ISBN: 978-1-4503-4783-9. Conference Chair Prof. Dr. Q. M. Jonathan Wu, University of Windsor, Canada Prof. Xudong Jiang, Nanyang Technological University, Singapore Submission Methods 1. Full Paper […]

Paper Publication This conference is supported by IEEE.The proceedings will be submitted and reviewed by the IEEE Xplore and Ei Compendex after the conference. Paper Topic (http://www.acirs.org/cfp.html) Underwater/Aerial Robots, Agriculture Robots, Space Robotics, Biomimetic robotics, Intelligent Transport Systems, Networked robots, Mobiligence, Rescue Robots, SWARM Intelligent Robots, Domestic Personal Robots, Visual Servoing/Robot vision, Medical/rehabilitation robotics, Perception/Learning, […]

Paper Publication The paper accepted by ICGIP 2017 will be published in conference proceedings in the SPIE Digital Library along with nearly 300,000 papers from other outstanding conferences and articles from SPIE Journals, which will be included in the SPIE Digital Library, and provided to the Web of Science (CPCI), *Scopus, Ei Compendex*, Inspec, Google […]

Publication All accepted papers must be written in English and will be published in IEEE conference proceedings and indexed by Ei Compendex and Scopus after conference. Submission 1. Full paper(publication and presentation) 2. Abstract (presentation) For full paper, please upload it to the Electronic Submission System (.pdf) https://www.easychair.org/conferences/?conf=icivc2017 For abstract, please send it to icivc@young.ac.cn […]

Population annealing is a promising recent approach for Monte Carlo simulations in statistical physics, in particular for the simulation of systems with complex free-energy landscapes. It is a hybrid method, combining importance sampling through Markov chains with elements of sequential Monte Carlo in the form of population control. While it appears to provide algorithmic capabilities […]