Leveraging Interactivity and MPI for Environmental Applications

This paper describes two different approaches to exploiting interactivity and MPI support available in the Interactive European Grid project.The first application is an air pollution simulation using Lagrangian trajectory model to simulate the spread of pollutant particles released into the atmosphere. The performance of the sequential implementation of the application was not satisfactory, therefore a parallelization was planned. The MPI programming model was used because of some previous experience with it and its support in the grid infrastructure to be used. Then the interactivity enabling the user to receive visualizations of simulation steps and to exercise control over the application running in the grid was added. The user interface for interacting with the application was implemented as a plug-in into the Migrating Desktop user interface client platform. The other application is an interactive workflow management system, which is a modification of a previously developed system for management of applications composed of web and grid services. It allows users to manage more complex jobs, composed of several program executions, in an interactive and comfortable manner. The system uses the interactive channel of the project to forward commands from a GUI to the on-site workflow manager, and to control the job during execution. This tool is able to visualize the inner workflow of the application. User has complete in-execution control over the job, can see its partial results, and can even alter it while it is running. This allows not only to accommodate the job workflow to the data it produces, extend or shorten it, but also to interactively debug and tune the job

Towards Distributed Petascale Computing

In this chapter we will argue that studying such multi-scale multi-science systems gives rise to inherently hybrid models containing many different algorithms best serviced by different types of computing environments (ranging from massively parallel computers, via large-scale special purpose machines to clusters of PC's) whose total integrated computing capacity can easily reach the PFlop/s scale. Such hybrid models, in combination with the by now inherently distributed nature of the data on which the models `feed' suggest a distributed computing model, where parts of the multi-scale multi-science model are executed on the most suitable computing environment, and/or where the computations are carried out close to the required data (i.e. bring the computations to the data instead of the other way around). We presents an estimate for the compute requirements to simulate the Galaxy as a typical example of a multi-scale multi-physics application, requiring distributed Petaflop/s computational power.Comment: To appear in D. Bader (Ed.) Petascale, Computing: Algorithms and Applications, Chapman & Hall / CRC Press, Taylor and Francis Grou

Management of Data Access with Quality of Service in PL-Grid Environment

e-Science applications increasingly require both computational power and storage resources, currently supported with a certain level of quality. Since in the grid and cloud environments, where we can execute the e-Science applications, heterogeneity of storage systems is higher than that of computational power resources, optimization of data access defines one of challenging tasks nowadays. In this paper we present our approach to management of data access in the grid environment. The main issue is to organize data in such a way that users requirements in the form of QoS/SLA are met. For this purpose we make use of a storage monitoring system and a mass storage system model -- CMSSM. The experiments are performed in the PL-Grid environment

Semantic-Oriented Performance Monitoring of Distributed Applications

Monitoring services are an essential component of large-scale computing infrastructures due to providing information which can be used by humans as well as applications to closely follow the progress of computations, to evaluate the performance of ongoing computing, etc. However, the users are usually left alone with performance measurements as to the interpreting and detecting of execution flaws. In this paper we present an approach to the performance monitoring of distributed applications based on semantic information about the monitored objects involved in the application execution. This allows to automate the guidance on what to measure further to come to a source of performance flaws as well to enable reacting on interesting events, e.g. on exceeding SLA parameters. Our research comprises the implementation of a robust system with semantics, which is not biased to an underlying ``physical'' monitoring system, giving the end user the power of intelligent monitoring functionality as well as the independence of the heterogeneity of distributed infrastructures

Use of Self-Healing Techniques for Highly-Available Distributed Monitoring

The paper addresses the self-healing aspects of the monitoring systems. Nowadays, when the complex distributed systems are concerned, the monitoring system should become "intelligent" - as the first step it can guide the user what should be monitored. The next level of the "intelligence" can be described by the term "self-healing". The goal is to provide the capability that a decision made automatically by the monitoring system should force the system under monitoring to behave more stable, reliable and predictable. In the paper a new monitoring system is presented: AgeMon is an agent based, distributed monitoring system with strictly defined roles which can be performed by the agents. In the paper we discuss self-healing in the context of monitoring. When the self-healing of the monitoring system is concerned, a good example is the case where it is possible to lose the monitoring data due to the storage problems. AgeMon can handle such problems and automatically elects substitute persistence agents to store the data

Semantic Grid Technologies in Computer Integrated Construction

Important goal of computer science in civil engineering projects is to facilitate dynamic collaboration among the companies, improvements of services and reuse of programs, data, information and knowledge. Civil engineering has some specific requirements concerning computer applications, which arise from the irrepeatability and scale of particular civil engineering products, processes and collaborating groups. Internet technologies are basis for linking processes in all construction phases, which leads to computer integrated construction. Computing grid, or shortly grid is a service infrastructure, which is being developed to facilitate infinite and seamless sharing of widely distributed, heterogeneous resources, hence, contributing towards the solution of complex engineering problems. A hypothesis of this work is that the grid can become viable platform for computer integrated construction, if semantic technologies are used for its development, i.e. ontologies and metadata, information, ontology and resource broker grid services. The hypothesis is tested by developing an ontology that defines the concept of a grid resource to describe specific resources in a grid environment. The aforementioned grid services are included in the design of a grid system, and are developed and deployed in a test bed. The test bed allows for the execution of complex grid applications, which take the form of workflows. It is shown that the ontology and the metadata about grid resources are useful when enabling, discovering, selecting and dynamically integrating resources on the grid. This approach yields several improvements against existing systems: a higher level of abstraction when developing and executing innovative and powerful engineering applications, greater flexibility, resource utilization and security, which is very important for dynamic collaboration within virtual organizations