New Science Gateways for Advanced Computing Simulations and Visualization Using Vine Toolkit in PL-Grid

A Science Gateway is a connection between scientists and their computational tools in the form of web portal. It creates a space for communities, collaboration and data sharing and visualization in a comprehensive and efficient manner. The main purpose of such a solution is to allow users to access the computational resources, process and analyze their data and get the results in a uniform and user friendly way. In this paper we propose a complex solution based on the Rich Internet Application (RIA) approach consisting of a web portal powered by Vine Toolkit with Adobe Flex/BlazeDs technologies. There are two Science Gateways described in detail one for engineers to manage computationally intensive workflows used in advanced airplane construction simulations, and one for nanotechnology scientists to manage experiments in nano-science field calculated with Density Functional Theory (DFT). In both cases the results show how modern web solution can help scientists in their work. &nbsp

QR Factorization of Tall and Skinny Matrices in a Grid Computing Environment

Previous studies have reported that common dense linear algebra operations do not achieve speed up by using multiple geographical sites of a computational grid. Because such operations are the building blocks of most scientific applications, conventional supercomputers are still strongly predominant in high-performance computing and the use of grids for speeding up large-scale scientific problems is limited to applications exhibiting parallelism at a higher level. We have identified two performance bottlenecks in the distributed memory algorithms implemented in ScaLAPACK, a state-of-the-art dense linear algebra library. First, because ScaLAPACK assumes a homogeneous communication network, the implementations of ScaLAPACK algorithms lack locality in their communication pattern. Second, the number of messages sent in the ScaLAPACK algorithms is significantly greater than other algorithms that trade flops for communication. In this paper, we present a new approach for computing a QR factorization -- one of the main dense linear algebra kernels -- of tall and skinny matrices in a grid computing environment that overcomes these two bottlenecks. Our contribution is to articulate a recently proposed algorithm (Communication Avoiding QR) with a topology-aware middleware (QCG-OMPI) in order to confine intensive communications (ScaLAPACK calls) within the different geographical sites. An experimental study conducted on the Grid'5000 platform shows that the resulting performance increases linearly with the number of geographical sites on large-scale problems (and is in particular consistently higher than ScaLAPACK's).Comment: Accepted at IPDPS10. (IEEE International Parallel & Distributed Processing Symposium 2010 in Atlanta, GA, USA.

The Living Application: a Self-Organising System for Complex Grid Tasks

We present the living application, a method to autonomously manage applications on the grid. During its execution on the grid, the living application makes choices on the resources to use in order to complete its tasks. These choices can be based on the internal state, or on autonomously acquired knowledge from external sensors. By giving limited user capabilities to a living application, the living application is able to port itself from one resource topology to another. The application performs these actions at run-time without depending on users or external workflow tools. We demonstrate this new concept in a special case of a living application: the living simulation. Today, many simulations require a wide range of numerical solvers and run most efficiently if specialized nodes are matched to the solvers. The idea of the living simulation is that it decides itself which grid machines to use based on the numerical solver currently in use. In this paper we apply the living simulation to modelling the collision between two galaxies in a test setup with two specialized computers. This simulation switces at run-time between a GPU-enabled computer in the Netherlands and a GRAPE-enabled machine that resides in the United States, using an oct-tree N-body code whenever it runs in the Netherlands and a direct N-body solver in the United States.Comment: 26 pages, 3 figures, accepted by IJHPC

Foundations of distributed multiscale computing: Formalization, specification, and analysis

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Patterns for High Performance Multiscale Computing

We describe our Multiscale Computing Patterns software for High Performance Multiscale Computing. Following a short review of Multiscale Computing Patterns, this paper introduces the Multiscale Computing Patterns Software, which consists of description, optimisation and execution components. First, the description component translates the task graph, representing a multiscale simulation, to a particular type of multiscale computing pattern. Second, the optimisation component selects and applies algorithms to find the most suitable mapping between submodels and available HPC resources. Third, the execution component which a middleware layer maps submodels to the number and type of physical resources based on the suggestions emanating from the optimisation part together with infrastructure-specific metrics such as queueing time and resource availability. The main purpose of the Multiscale Computing Patterns software is to leverage the Multiscale Computing Patterns to simplify and automate the execution of complex multiscale simulations on high performance computers, and to provide both application-specific and pattern-specific performance optimisation. We test the performance and the resource usage for three multiscale models, which are expressed in terms of two Multiscale Computing Patterns. In doing so, we demonstrate how the software automates resource selection and load balancing, and delivers performance benefits from both the end-user and the HPC system level perspectives

Putting the User at the Centre of the Grid: Simplifying Usability and Resource Selection for High Performance Computing

Computer simulation is finding a role in an increasing number of scientific disciplines, concomitant with the rise in available computing power. Realizing this inevitably re- quires access to computational power beyond the desktop, making use of clusters, supercomputers, data repositories, networks and distributed aggregations of these re- sources. Accessing one such resource entails a number of usability and security prob- lems; when multiple geographically distributed resources are involved, the difficulty is compounded. However, usability is an all too often neglected aspect of computing on e-infrastructures, although it is one of the principal factors militating against the widespread uptake of distributed computing. The usability problems are twofold: the user needs to know how to execute the applications they need to use on a particular resource, and also to gain access to suit- able resources to run their workloads as they need them. In this thesis we present our solutions to these two problems. Firstly we propose a new model of e-infrastructure resource interaction, which we call the user–application interaction model, designed to simplify executing application on high performance computing resources. We describe the implementation of this model in the Application Hosting Environment, which pro- vides a Software as a Service layer on top of distributed e-infrastructure resources. We compare the usability of our system with commonly deployed middleware tools using five usability metrics. Our middleware and security solutions are judged to be more usable than other commonly deployed middleware tools. We go on to describe the requirements for a resource trading platform that allows users to purchase access to resources within a distributed e-infrastructure. We present the implementation of this Resource Allocation Market Place as a distributed multi- agent system, and show how it provides a highly flexible, efficient tool to schedule workflows across high performance computing resources

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