Computational steering and the SCIRun integrated problem solving environment

Journal ArticleSCIRun is a problem solving environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. We review related systems and introduce a taxonomy that explores different computational steering solutions. Considering these approaches, we discuss why a tightly integrated problem solving environment, such as SCIRun, simplifies the design and debugging phases of computational science applications and how such an environment aids in the scientific discovery process

CUMULVS: Collaborative infrastructure for developing distributed simulations

The CUMULVS software environment provides remote collaboration among scientists by allowing them to dynamically attach to, view, and steer a running simulation. Users can interactively examine intermediate results on demand, saving effort for long-running applications gone awry. In addition, it provides fault tolerance to distributed applications via user-directed checkpointing, heterogeneous task migration and automatic restart. This talk describes CUMULVS and how this tool benefits scientists developing large distributed applications

A Component Architecture for High-Performance Scientific Computing

The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance computing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individuals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed computing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal overhead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including combustion research, global climate simulation, and computational chemistry

An interactive design environment for coal piping system

The design of coal piping system of a coal-fired power plant is a complex and time-consuming engineering task that involves meeting of several design objectives and constraints. The distribution of coal particles in a pneumatic pipeline can be highly inhomogeneous. Current coal piping design technology relies on empirical model and does not consider particle distribution characteristics in the pipe. In this thesis, a design tool which couples a validated detailed pipe model and an interactive optimization algorithm is developed. This new design tool uses evolutionary algorithms (EAs) as the optimization algorithm, and computational fluid dynamics (CFD) as the evaluation mechanism. The process uses an iterative approach that allows design to be evaluated using CFD analysis automatically to optimize several criteria. The proposed design change is then re-meshed and displayed. Three fundamentally different techniques from traditional optimization methods were considered in order to reduce computation time. Firstly, the tool has been implemented in a virtual engineering environment using VE-Suite. Secondly, the system is integrated with a general interface to allow users to set up the design procedure and interact or guide the searching path as the design evolves. Thirdly, a fast calculation approach is used to reduce the time for single CFD case. The proposed interactive design tool is analyzed and enhanced so that it is usable by the general engineering community. A real coal pipe application was carried out using this design tool. The main objective is to distribute coal flow to its two branches as uniform as possible. The results of this work suggested that the optimum coal pipe can be found relatively fast even when using high-fidelity CFD solver as the analysis method, and the optimum pipe can greatly reduce the coal flow unbalance. This indicates that the tool presented in this thesis can be used as a new and efficient design environment for coal pipe

An integrated software approach to interactive exploration and steering of fluid flow simulations on many-core architectures

Traditionell werden numerische Strömungssimulationen in einer zyklischen Sequenz autonomer Teilschritte durchgeführt. Seitens Wissenschaftlern existiert jedoch schon lange der Wunsch nach mehr Interaktion mit laufenden Simulationen. Seit dem maßgeblichen Report der National Science Foundation im Jahre 1987 wurden daher neue Formen der wissenschaftlichen Visualisierung entwickelt, die sich grundlegend von den traditionellen Verfahren unterscheiden. Insbesondere hat der sogenannte Computational Steering-Ansatz reges Interesse bewirkt. Damals wie heute ist die Anwendung des Verfahrens jedoch eher die Ausnahme denn die Regel. Ursächlich dafür sind zu großen Teilen Komplexität und Restriktionen traditioneller Hochleistungssysteme. Im Rahmen dieser Arbeit wird daher als Alternative zu dem traditionellen Vorgehen die immense Leistungsfähigkeit moderner Grafikkartengenerationen für die Berechnungen herangezogen. Das sogenannte GPGPU-Computing eignet sich insbesondere für die Anwendung der Lattice-Boltzmann-Methode im Bereich numerischer Strömungssimulationen. Auf Grundlage des LBM-Verfahrens wird im Rahmen dieser Arbeit prototypisch eine interaktive Simulationsumgebung basierend auf dem Computational Steering-Paradigma entwickelt, das alle Prozesse zur Lösung von Strömungsproblemen innerhalb einer einzelnen Anwendung integriert. Durch die Konvergenz der hohen massiv parallelen Rechenleistung der GPUs und der Interaktionsfähigkeiten in einer einzelnen Anwendung kann eine erhebliche Steigerung der Anwendungsqualität erzielt werden. Dabei ist es durch Einsatz mehrerer GPUs möglich, dreidimensionale Strömungsprobleme mit praxisrelevanter Problemgröße zu berechnen und gleichzeitig eine interaktive Manipulation und Exploration des Strömungsgebiets zur Laufzeit zu ermöglichen. Dabei ist der erforderliche finanzielle Aufwand verglichen mit traditionellen massiv parallelen Verfahren verhältnismäßig gering.Traditionally, computational fluid dynamics is done in a cyclic sequence of independent steps. Howerver it is a long term wish of scientists and engineers to closely interact with their running simulations. Since the influential report of the US National Science Foundation in 1987 new forms of scientific visualization have evolved that are quite different from traditional post-processing. Especially the approach commonly referred to as computational steering has been the subject of widespread interest. Although it is a very powerful paradigm, the use of computational steering is still the exception rather than the rule. The reasons for this are more or less related to the complexity and restrictions of traditional HPC systems. As an alternative to the traditional massively parallel approach, in this thesis the parallel computational power of GPGPUs is used for general purpose applications. The so called GPGPU computing has gained large popularity in the CFD community, especially for its application to the lattice Boltzmann method. Using this technology this work demonstrates a single desktop application integrating a complete interactive CFD simulation environment for reasonable hardware costs. It shows that the convergence of massive parallel computational power and steering environment into a single system significantly improves the usability, application quality and user-friendliness. Using multiple GPUs, the efficiency of this approach allows for CFD simulations in three dimensional space evolving close to real-time even for reasonable grid sizes. Thereby, the simulation can be explored and also adjusted during runtime. The thesis also shows that the responsiveness significantly benefits from avoiding common bandwidth and latency bottlenecks inherent in traditional HPC approaches. Those can be avoided as GPGPU computing does not generally require network communication, which also reduces the complexity of the application

An agent-based visualisation system.

This thesis explores the concepts of visual supercomputing, where complex distributed systems are used toward interactive visualisation of large datasets. Such complex systems inherently trigger management and optimisation problems; in recent years the concepts of autonomic computing have arisen to address those issues. Distributed visualisation systems are a very challenging area to apply autonomic computing ideas as such systems are both latency and compute sensitive, while most autonomic computing implementations usually concentrate on one or the other but not both concurrently. A major contribution of this thesis is to provide a case study demonstrating the application of autonomic computing concepts to a computation intensive, real-time distributed visualisation system. The first part of the thesis proposes the realisation of a layered multi-agent system to enable autonomic visualisation. The implementation of a generic multi-agent system providing reflective features is described. This architecture is then used to create a flexible distributed graphic pipeline, oriented toward real-time visualisation of volume datasets. Performance evaluation of the pipeline is presented. The second part of the thesis explores the reflective nature of the system and presents high level architectures based on software agents, or visualisation strategies, that take advantage of the flexibility of the system to provide generic features. Autonomic capabilities are presented, with fault recovery and automatic resource configuration. Performance evaluation, simulation and prediction of the system are presented, exploring different use cases and optimisation scenarios. A performance exploration tool, Delphe, is described, which uses real-time data of the system to let users explore its performance