high performance computing on graphics processing units: hgpu.org

In this paper, we introduce an interactive coastal wave simulation and visualization software, called Celeris. Celeris is an open source software which needs minimum preparation to run on a Windows machine. The software solves the extended Boussinesq equations using a hybrid finite volume – finite difference method and supports moving shoreline boundaries. The simulation and […]

Performance and an aspect of it, energy efficiency, has become a key issue in both high performance and embedded computing. The objective of the 2nd TAPEMS International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation is to bring together researchers and practitioners from academia and industry to discuss current advances and trends in theoretical […]

The primary goal of the conference is to promote research and developmental activities in Bioinformatics and Biomedical Technology. Another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in Portugal and abroad. The conference will be held every year to make it an ideal platform for people to share […]

The objective of the 2017 7th International Conference on Biomedical Engineering and Technology (ICBET 2017) is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Biomedical Engineering and Technology. 2017 7th International Conference on Biomedical Engineering and […]

You are cordially invited to join us at the International Conference on High Performance Compilation, Computing and Communications (HP3C-2017) in Kuala Lumpur, Malaysia during March 22-24, 2017, with the sponsor of American Society for Research. With the rapid growth in computing and communications technology, the past decade has witnessed a proliferation of powerful parallel and […]

Particle filter is one promising method to estimate the internal states in dynamical systems, and can be used for various applications such as visual tracking and mobile-robot localization. The major drawback of particle filter is its large computational amount, which causes long computational-time and large powerconsumption. In order to solve this problem, this paper proposes […]

Domain-Specific Languages (DSLs) provide high-level and domain-specific abstractions that allow expressive and concise algorithm descriptions. Since the description in a DSL hides also the properties of the target hardware, DSLs are a promising path to target different parallel and heterogeneous hardware from the same algorithm description. In theory, the DSL description can capture all characteristics […]

Training time on large datasets for deep neural networks is the principal workflow bottleneck in a number of important applications of deep learning, such as object classification and detection in automatic driver assistance systems (ADAS). To minimize training time, the training of a deep neural network must be scaled beyond a single machine to as […]

Sorting is a well interrogating issue in computer science. Many authors have invented numerous sorting algorithms on CPU (Central Processing Unit). In today’s life sorting on the CPU is not so efficient. To get the efficient sorting parallelization should be done. There are many ways of parallelization of sorting but at the present time GPU […]

In this article we will explore the OpenACC platform for programming Graphics Processing Units (GPUs). The OpenACC platform offers a directive based programming model for GPUs which avoids the detailed data flow control and memory management necessary in a CUDA programming environment. In the OpenACC model, programs can be written in high level languages with […]

A Graphics Processing Unit (GPU) is a parallel computing coprocessor specialized in accelerating vector operations. The enormous heterogeneity of parallel computing platforms justifies and motivates the development of automated optimization tools and techniques. The Algorithm Selection Problem consists in finding a combination of algorithms, or a configuration of an algorithm, that optimizes the solution of […]

We consider the problem of how to reduce the cost of communication that is required for the parallel training of a neural network. The state-of-the-art method, Bulk Synchronous Parallel Stochastic Gradient Descent (BSP-SGD), requires many collective communication operations, like broadcasts of parameters or reductions for sub-gradient aggregations, which for large messages quickly dominates overall execution […]