Overcoming engineering challenges of providing an effective user interface to a large scale distributed synthetic environment on the US teragrid: a systems engineering success story

Over recent years’ large-scale distributed synthetic environment enterprises have been evolving in a diverse range of scientific and engineering fields. These computer modelling and simulation systems are increasing in scale and dimension in order to allow scientists and engineers to explore the attributes and emergent properties of a given system design. Within the field of computational science, the grid facilitates very large-scale collaborative simulation enterprises. The grid is similar to distributed interactive simulation/high level architecture (DIS/HLA) in that it supports interconnectivity but differs in the sense that it supports intercommunication of large super computing resources. An important factor in the rapid adoption of the grid has been its role in enabling access to significant supercomputing resources not usually available at a single institution. However, the major challenge for the grid has been the lack of an effective and ubiquitous interface to the huge computational resource (which can comprise over 6000 CPUs distributed across the globe) at any time and from any location. This paper describes a unique user interface built on systems engineering principles and practices to solve the problem of delivering real-time interaction (from lightweight computing devices such as personal digital assistants, commonly known as tablet devices, to high end computing platforms) with simulations delivering high resolution 3D images. The application of our work has far reaching benefits for many sectors including: aerospace, medical informatics, engineering design, distributed simulation, and modelling

Workshop on Grid Generation and Related Areas

A collection of papers given at the Workshop on Grid Generation and Related Areas is presented. The purpose of this workshop was to assemble engineers and scientists who are currently working on grid generation for computational fluid dynamics (CFD), surface modeling, and related areas. The objectives were to provide an informal forum on grid generation and related topics, to assess user experience, to identify needs, and to help promote synergy among engineers and scientists working in this area. The workshop consisted of four sessions representative of grid generation and surface modeling research and application within NASA LeRC. Each session contained presentations and an open discussion period

Resource Management Services for a Grid Analysis Environment

Selecting optimal resources for submitting jobs on a computational Grid or accessing data from a data grid is one of the most important tasks of any Grid middleware. Most modern Grid software today satisfies this responsibility and gives a best-effort performance to solve this problem. Almost all decisions regarding scheduling and data access are made by the software automatically, giving users little or no control over the entire process. To solve this problem, a more interactive set of services and middleware is desired that provides users more information about Grid weather, and gives them more control over the decision making process. This paper presents a set of services that have been developed to provide more interactive resource management capabilities within the Grid Analysis Environment (GAE) being developed collaboratively by Caltech, NUST and several other institutes. These include a steering service, a job monitoring service and an estimator service that have been designed and written using a common Grid-enabled Web Services framework named Clarens. The paper also presents a performance analysis of the developed services to show that they have indeed resulted in a more interactive and powerful system for user-centric Grid-enabled physics analysis.Comment: 8 pages, 7 figures. Workshop on Web and Grid Services for Scientific Data Analysis at the Int Conf on Parallel Processing (ICPP05). Norway June 200

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

Adaptive remote visualization system with optimized network performance for large scale scientific data

This dissertation discusses algorithmic and implementation aspects of an automatically configurable remote visualization system, which optimally decomposes and adaptively maps the visualization pipeline to a wide-area network. The first node typically serves as a data server that generates or stores raw data sets and a remote client resides on the last node equipped with a display device ranging from a personal desktop to a powerwall. Intermediate nodes can be located anywhere on the network and often include workstations, clusters, or custom rendering engines. We employ a regression model-based network daemon to estimate the effective bandwidth and minimal delay of a transport path using active traffic measurement. Data processing time is predicted for various visualization algorithms using block partition and statistical technique. Based on the link measurements, node characteristics, and module properties, we strategically organize visualization pipeline modules such as filtering, geometry generation, rendering, and display into groups, and dynamically assign them to appropriate network nodes to achieve minimal total delay for post-processing or maximal frame rate for streaming applications. We propose polynomial-time algorithms using the dynamic programming method to compute the optimal solutions for the problems of pipeline decomposition and network mapping under different constraints. A parallel based remote visualization system, which comprises a logical group of autonomous nodes that cooperate to enable sharing, selection, and aggregation of various types of resources distributed over a network, is implemented and deployed at geographically distributed nodes for experimental testing. Our system is capable of handling a complete spectrum of remote visualization tasks expertly including post processing, computational steering and wireless sensor network monitoring. Visualization functionalities such as isosurface, ray casting, streamline, linear integral convolution (LIC) are supported in our system. The proposed decomposition and mapping scheme is generic and can be applied to other network-oriented computation applications whose computing components form a linear arrangement

High Performance Air Quality Simulation in the European CrossGrid Project

This paper focuses on one of the applications involved into the CrossGrid project, the STEM-II air pollution model used to simulate the environment of As Pontes Power Plant in A Coruna (Spain). The CrossGrid project offers us a Grid environment oriented towards computation- and data-intensive applications that need interaction with an external user. The air pollution model needs the interaction of an expert in order to make decisions about modifications in the industrial process to fulfil the European standard on emissions and air quality. The benefits of using different CrossGrid components for running the application on a Grid infrastructure are shown in this paper, and some preliminary results on the CrossGrid testbed are displayed

A Distributed System for Parallel Simulations

We presented the technologies and algorithms to build a web-based visualization and steering system to monitor the dynamics of remote parallel simulations executed on a Linux Cluster. The polynomial time based algorithm to optimally utilize distributed computing resources over a network to achieve maximum frame-rate was also proposed. Keeping up with the advancements in modern web technologies, we have developed an Ajax-based web frontend which allows users to remotely access and control ongoing computations via a web browser facilitated by visual feedbacks in real-time. Experimental results are also given from sample runs mapped to distributed computing nodes and initiated by users at different geographical locations. Our preliminary results on frame-rates illustrated that system performance was affected by network conditions of the chosen mapping loop including available network bandwidth and computing capacities. The underlying programming framework of our system supports mixed-programming mode and is flexible to integrate most serial or parallel simulation code written in different programming languages such as Fortran, C and Java

Agentless robust load sharing strategy for utilising hetero-geneous resources over wide area network

Resource monitoring and performance prediction services have always been regarded as important keys to improving the performance of load sharing strategy. However, the traditional methodologies usually require specific performance information, which can only be collected by installing proprietary agents on all participating resources. This requirement of implementing a single unified monitoring service may not be feasible because of the differences in the underlying systems and organisation policies. To address this problem, we define a new load sharing strategy which bases the load decision on a simple performance estimation that can be measured easily at the coordinator node. Our proposed strategy relies on a stage-based dynamic task allocation to handle the imprecision of our performance estimation and to correct load distribution on-the-fly. The simulation results showed that the performance of our strategy is comparable or better than traditional strategies, especially when the performance information from the monitoring service is not accurate