Graphical modeling is a method that is increasingly being used to model real-life applications such as medical diagnosis, security and emergency response systems, and computer vision. A graphical model represents random variables and dependencies between them by means of a graph, in which some variables may not be observable in practice. An important problem in graphical models is that of infer...

We present the implementation of a full electronic structure calculation code on a hybrid parallel architecture with graphic processing units (GPUs). This implementation is performed on a free software code based on Daubechies wavelets. Such code shows very good performances, systematic convergence properties, and an excellent efficiency on parallel computers. Our GPU-based acceleration fully p...

In this paper, we present several techniques of digital image processing that can be used in the recovering of damaged graphical documents. The ancient graphical documents give an important information in several subjects like history, ethnography or architecture reconstruction and then a good conservation and recovering is an important issue. The techniques presented are especially important w...

The Time Dependent Ginzburg Landau(TDGL) equation models a complex scalar field and is used to study a variety of different physical systems and exhibits phase transitional behaviours that necessitate study using numerical simulation methods. We employ fast data-parallel simulation algorithms on Graphical Processing Units (GPUs) and report on performance data and stability tradeoffs from using ...

Thanks to the recent technological advances, a large variety of image data is at our disposal with variable geometric, radiometric and temporal resolution. In many applications the processing of such images needs high performance computing techniques in order to deliver timely responses e.g. for rapid decisions or real-time actions. Thus, parallel or distributed computing methods, Digital Signa...

Graphical Processing Units (GPUs) are good data-parallel performance accelerators for solving regular mesh partial differential equations (PDEs) whereby low-latency communications and high compute to communications ratios can yield very high levels of computational efficiency. Finite-difference time-domain methods still play an important role for many PDE applications. Iterative multi-grid and ...

Complex networks are often studied using statistical measurements over many independently generated samples. Irregular data structures such as graphs that involve dynamical memory management and “pointer chasing” are an important class of application and have attracted recent interest in the form of the Graph500 benchmark formulation. The generation of simulated sample network graphs and measur...

The movement of poorly sorted material over steep areas constitutes a hazardous environmental problem. Computational tools help in the understanding and predictions of such landslides. The main drawback is the high computational effort required for obtaining accurate numerical solutions due to the high number of cells involved in the calculus. In order to overcome this problem, this work propos...

The article reviews studies that explain the role of graphical displays in learning and synthesizes relevant findings into principles for effective graphical design. Three theoretical perspectives provide the framework that organizes the review: dual coding theory, visual argument, and conjoint retention. The three theories are compatible although they are based on different assumptions. Resear...