The geosciences, particularly numerical weather prediction, are demanding the highest levels of available computer power. The European Centre for Medium-Range Weather Forecasts, with its experience in using supercomputers in this field, organises every second year a workshop bringing together manufacturers, computer scientists, researchers and operational users to share their experiences and to learn about the latest developments. This book reports on the November 2000 workshop. It provides an excellent overview of the latest achievements in, and plans for the use of, new parallel techniques in meteorology, climatology and oceanography.

Geosciences and in particular numerical weather prediction are demanding the highest levels of available computer power. The European Centre for Medium-Range Weather Forecasts, with its experience in using supercomputers in this field, organizes every other year a workshop bringing together manufacturers, computer scientists, researchers and operational users to share their experiences and to learn about the latest developments. This book provides an excellent overview of the latest achievements in and plans for the use of new parallel techniques in meteorology, climatology and oceanography. The proceedings have been selected for coverage in: . OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)."

This book constitutes the refereed proceedings of the 20th Iberoamerican Congress on Pattern Recognition, CIARP 2015, held in Montevideo, Uruguay, in November 2015. The 95 papers presented were carefully reviewed and selected from 185 submissions. The papers are organized in topical sections on applications on pattern recognition; biometrics; computer vision; gesture recognition; image classification and retrieval; image coding, processing and analysis; segmentation, analysis of shape and texture; signals analysis and processing; theory of pattern recognition; video analysis, segmentation and tracking.

This title includes a number of Open Access chapters.Earth science is a broad field of study that encompasses many different disciplines, including meteorology, climatology, and geology. The importance of the earth sciences-in predicting weather and climate, tracking pollution, drilling for petroleum, evaluating soil, and monitoring ground water-is

Parallel Programming with Co-Arrays describes the basic techniques used to design parallel algorithms for high-performance, scientific computing. It is intended for upper-level undergraduate students and graduate students who need to develop parallel codes with little or no previous introduction to parallel computing. It is also intended as a reference manual for researchers active in the field of scientific computing. All the algorithms in the book are based on partition operators. These operators provide a unifying principle that fits seemingly disparate techniques into an overall framework for algorithm design. The book uses the co-array programming model to illustrate how to write code for concrete examples, but it emphasizes that the important concepts for algorithm design are independent of the programming model. With these concepts in mind, the reader can write algorithms in different programming models based on personal taste and comfort.

Collected articles in this series are dedicated to the development and use of software for earth system modelling and aims at bridging the gap between IT solutions and climate science. The particular topic covered in this volume addresses the historical development, state of the art and future perspectives of the mathematical techniques employed for numerical approximation of the equations describing atmospheric and oceanic motion. Furthermore, it describes the main computer science and software engineering strategies employed to turn these mathematical methods into effective tools for understanding earth's climate and forecasting its evolution. These methods and the resulting computer algorithms lie at the core of earth system models and are essential for their effectiveness and predictive skill.

Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer’s silicon test tube, there is need for precise and computable process descriptions. The scienti?c ?elds of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model’s complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.