Computational Methods in Science and Engineering : Proceedings of the Workshop SimLabs@KIT, November 29 - 30, 2010, Karlsruhe, Germany

In this proceedings volume we provide a compilation of article contributions equally covering applications from different research fields and ranging from capacity up to capability computing. Besides classical computing aspects such as parallelization, the focus of these proceedings is on multi-scale approaches and methods for tackling algorithm and data complexity. Also practical aspects regarding the usage of the HPC infrastructure and available tools and software at the SCC are presented

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

Two major trends in computing hardware during the last decade have been an increase in the number of processing cores found in individual computer hardware platforms and an ubiquity of distributed, heterogeneous systems. Together, these changes can improve not only the performance of a range of applications, but the types of applications that can be created. Despite the advances in hardware technology, advances in programming of such systems has not kept pace. Traditional concurrent programming has always been challenging, and is only set to be come more so as the level of hardware concurrency increases. The different hardware platforms which make up heterogeneous systems come with domain-specific programming models, which are not designed to interact, or take into account the different resource-constraints present across different hardware devices, motivating a need for runtime reconfiguration or adaptation. This dissertation investigates the actor model of computation as an appropriate abstraction to address the issues present in programming concurrent, distributed, and adaptive applications across different scales and types of computing hardware. Given the limitations of other approaches, this dissertation describes a new actor-based programming language (Ensemble) and its runtime to address these challenges. The goal of this language is to enable non-specialist programmers to take advantage of parallel, distributed, and adaptive programming without the programmer requiring in-depth knowledge of hardware architectures or software frameworks. There is also a description of the design and implementation of the runtime system which executes Ensemble applications across a range of heterogeneous platforms. To show the suitability of the actor-based abstraction in creating applications for such systems, the language and runtime were evaluated in terms of linguistic complexity and performance. These evaluations covered programming embedded, concurrent, distributed, and adaptable applications, as well as combinations thereof. The results show that the actor provides an objectively simple way to program such systems without sacrificing performance

Multiscale, Multiphysics Modelling of Coastal Ocean Processes: Paradigms and Approaches

This Special Issue includes papers on physical phenomena, such as wind-driven flows, coastal flooding, and turbidity currents, and modeling techniques, such as model comparison, model coupling, parallel computation, and domain decomposition. These papers illustrate the need for modeling coastal ocean flows with multiple physical processes at different scales. Additionally, these papers reflect the current status of such modeling of coastal ocean flows, and they present a roadmap with numerical methods, data collection, and artificial intelligence as future endeavors

Modelo computacional paralelo baseado em GPU para cálculo do campo de vento de um sistema de dispersão atmosférica de radionuclídeos

In order to improve the prediction of atmospheric dispersion of radionuclide (ADR) in vicinity of Central Nuclear Almirante Alvaro Alberto (CNAAA) Brazilian Nuclear Power Plants (NPP), a more refined computational system is under development. To achieve desired refinement, the required computational effort increases in such a way that system's execution by current computers leads to prohibitive processing time. Aiming to accelerate execution of such refined system, allowing its effective use in real-time prediction of ADR, a GPU-based parallel approach has been proposed. Basically, the ADR system used in CNAAA is comprised by 4 main modules (programs): Source Term, Wind Field, Plume Dispersion and Plume Projection modules. This work is focused on the Wind Field module, which uses a mass-consistent approach, based on Winds Extrapolated from Stability and Terrain (WEST) model. Due to the strong sequential nature of the algorithm, domain decomposition by a 3D-RedBlack partitioning was proposed and a new parallel GPU-based algorithm was implemented using the Compute Unified Device Architecture (CUDA) and C programming language. As a result, the execution time of a fine-grained simulation decreased from about 450 seconds (running on an Intel-I7) to 5,60 seconds (running on a GTX-680 GPU). Here, the most important issues of the parallel implementation, their optimization, as well as comparative results, are presented and discussed.Com o objetivo de melhorar a previsão da dispersão atmosférica de radionuclídeos (DAR) nas proximidades da Central Nuclear Brasileira Almirante Álvaro Alberto (CNAAA), está em desenvolvimento um sistema computacional mais refinado. Para alcançar o refinamento desejado, o esforço computacional necessário aumenta de tal forma que a execução do sistema pelos computadores atuais leva a um tempo de processamento proibitivo. Com o objetivo de acelerar a execução de tal sistema refinado, permitindo seu uso efetivo na previsão em tempo real da DAR, uma abordagem paralela baseada em GPU foi proposta. Basicamente, o sistema DAR usado no CNAAA é composto por 4 módulos principais (programas): Módulo Termo Fonte, Campo de Vento, Dispersão de Pluma e Módulos de Projeção de Pluma. Este trabalho é focado no módulo do Campo de Vento, que utiliza uma abordagem não divergente, com base no modelo Winds Extrapolated from Stability and Terrain (WEST). Devido à forte natureza sequencial do algoritmo, a decomposição do domínio por um particionamento 3D-Red-Black foi proposto e um novo algoritmo baseado em GPU paralelo foi implementado usando o Compute Unified Device Architecture (CUDA) e a linguagem de programação C. Como resultado, o tempo de execução de uma simulação de malha fina diminuiu de cerca de 450 segundos (executado em um Intel-I7) a 5,60 segundos (em execução em uma GPU GTX-680). Aqui, são apresentadas e discutidas as questões mais importantes da implementação paralela, sua otimização, bem como os resultados comparativos

Software for Exascale Computing - SPPEXA 2016-2019

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest

Accelerating Lagrangian Particle Dispersion in the Atmosphere with OpenCL Across Multiple Platforms

FLEXPART is a popular simulator that models the transport and diffusion of air pollutants, based on the Lagrangian approach. It is capable of regional and global simulation and supports both forward and backward runs. A complex model like this contains many calculations suitable for parallelisation. Recently, a GPU-accelerated version of the simulator (FLEXCPP) has been written in C++/CUDA. As CUDA is only supported on NVIDIA GPUs, such an implementation is tied to a single hardware vendor, and is not able to take advantage of other hardware acceleration platforms. This paper presents an OpenCL/C++ version of FLEXCPP, called FlexOcl. This simulator provides all the functionality of FLEXCPP, and has been extended to include modelling of the decay of radioactive particles. A performance comparison between the two simulators has been performed on GPU, and the performance of FlexOcl has also been evaluated on the Intel Xeon Phi, as well as a number of other hardware platforms. Our results show that the OpenCL code performs better than CUDA code on GPUs, and that equivalent performance is seen on the Xeon Phi for this type of application

Tracing back the source of contamination

From the time a contaminant is detected in an observation well, the question of where and when the contaminant was introduced in the aquifer needs an answer. Many techniques have been proposed to answer this question, but virtually all of them assume that the aquifer and its dynamics are perfectly known. This work discusses a new approach for the simultaneous identification of the contaminant source location and the spatial variability of hydraulic conductivity in an aquifer which has been validated on synthetic and laboratory experiments and which is in the process of being validated on a real aquifer