high performance computing on graphics processing units: hgpu.org

Nowadays, clusters containing multiple GPU nodes are widely used to execute high-performance computing applications. Diverse disciplines use these clusters to improve the performance of several services that consume high computational resources. The challenge of executing high-performance computing applications becomes harder when the applications are executed concurrently and each one of them may demand multiple GPU […]

The overall goal of this thesis is to evaluate the feasibility of FPGA based computer system in HPC. This works is performed within ExaNeSt, an EU funded project which aims to develop and prototype energy efficient solutions for the production of exascale-level supercomputers. As the matter of fact, the current computer architectures need to be […]

The recent popularity of deep neural networks (DNNs) has generated a lot of research interest in performing DNN-related computation efficiently. However, the primary focus is usually very narrow and limited to (i) inference — i.e. how to efficiently execute already trained models and (ii) image classification networks as the primary benchmark for evaluation. Our primary […]

Graphics Processing Units (GPUs) perform the majority of computations in state-of-the-art supercomputers. Programming these GPUs is often assisted using a programming model such as (amongst others) the directive-driven OpenACC. Unfortunately, OpenACC (and other similar models) are incapable of automatically targeting and distributing work across several GPUs, which decreases productivity and forces needless manual labor upon […]

International Conference on Biomedicine & Pharmacotherapy is going to be held during August 06-07, 2018 in Osaka, Japan. The conferences focuses on foremost topics such as Biomedicine, Biomedical Statistics, Biomedical Diagnosis, Frontiers in Biomedicine, Industrial Pharmacy, Pharmacotherapy, Molecular Biomedicine, Computational Biomedicine, Tissue Engineering, Medical Devices, Biomedical Model, Personalized Medicine, Biomedical Technology, Nanotechnology, Pharmacotherapy, Pharmaceutical Sciences, […]

Meeting time：June 28-30, 2018 Meeting place：1880 New Petchburi Road, Bangkok 10310 Thailand Organized by Science and Engineering Institute, co organized by Bauman Moscow State technical University, Russia, Tokyo University of Science, Japan and China Agricultural University, 2018 the 8th International Workshop on Computer Science and Engineering (WCSE 2018) to Bangkok, Thailand during June 28-30, 2018. […]

Mechatronics and Robotics 2018 warmly welcome all the researchers, developers, experts, students from the field of mechatronics & robotics to attend International Conference on Mechatronics & Robotics during October 15-16, 2018, Helsinki, Finland. The Conference will be composed around the theme “Unfolding Knowledge with a Delineate Technical World". Sessions covered as mentioned below: 1. Mechatronics […]

Meeting time: June 27-29, 2018 Meeting place: No.2 Chong Wen Road, Nan An District, Chongqing 400065, P. R. China Keynote speakers Prof. Lap-Pui Chau, Nanyang Technological University, Singapore (IEEE Fellow) Prof. Shahram Latifi, UNIVERSITY OF NEVADA, USA (IEEE Fellow) Published by: All accepted papers must be written in English and will be published into conference proceedings and indexed […]

Meeting time: June 23-25, 2018 Meeting place: Room 301, 2nd Floor, No.2 Teaching Building, West Area of the campus, No. 388 Lumo Road, Wuhan, P.R. China Keynote speakers Prof. Mengchu Zhou IEEE Fellow, IFAC Fellow, AAAS Fellow New Jersey Institute of Technology, USA Prof. Zhang Dan,  PhD, PEng., FCAE, FEIC, FASME, FCSME, SMIEEE Kaneff Research […]

In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation and development of CNNs, several software frameworks have been released, primarily targeting power-hungry CPUs and GPUs. In this context, reconfigurable hardware in the form of FPGAs constitutes a potential alternative platform that can be […]

We propose a parallel program representation for heterogeneous systems, designed to enable performance portability across a wide range of popular parallel hardware, including GPUs, vector instruction sets, multicore CPUs and potentially FPGAs. Our representation, which we call HPVM, is a hierarchical dataflow graph with shared memory and vector instructions. HPVM supports three important capabilities for […]

Latent Dirichlet Allocation(LDA) is a popular topic model. Given the fact that the input corpus of LDA algorithms consists of millions to billions of tokens, the LDA training process is very time-consuming, which may prevent the usage of LDA in many scenarios, e.g., online service. GPUs have benefited modern machine learning algorithms and big data […]