3 research outputs found
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
Support for flexible and transparent distributed computing
Modern distributed computing developed from the traditional supercomputing community rooted firmly
in the culture of batch management. Therefore, the field has been dominated by queuing-based resource
managers and work flow based job submission environments where static resource demands needed be
determined and reserved prior to launching executions. This has made it difficult to support resource
environments (e.g. Grid, Cloud) where the available resources as well as the resource requirements
of applications may be both dynamic and unpredictable. This thesis introduces a flexible execution
model where the compute capacity can be adapted to fit the needs of applications as they change during
execution. Resource provision in this model is based on a fine-grained, self-service approach instead
of the traditional one-time, system-level model. The thesis introduces a middleware based Application
Agent (AA) that provides a platform for the applications to dynamically interact and negotiate resources
with the underlying resource infrastructure.
We also consider the issue of transparency, i.e., hiding the provision and management of the distributed
environment. This is the key to attracting public to use the technology. The AA not only replaces
user-controlled process of preparing and executing an application with a transparent software-controlled
process, it also hides the complexity of selecting right resources to ensure execution QoS. This service
is provided by an On-line Feedback-based Automatic Resource Configuration (OAC) mechanism cooperating
with the flexible execution model. The AA constantly monitors utility-based feedbacks from the
application during execution and thus is able to learn its behaviour and resource characteristics. This
allows it to automatically compose the most efficient execution environment on the fly and satisfy any
execution requirements defined by users. Two policies are introduced to supervise the information learning
and resource tuning in the OAC. The Utility Classification policy classifies hosts according to their
historical performance contributions to the application. According to this classification, the AA chooses
high utility hosts and withdraws low utility hosts to configure an optimum environment. The Desired
Processing Power Estimation (DPPE) policy dynamically configures the execution environment according
to the estimated desired total processing power needed to satisfy usersā execution requirements.
Through the introducing of flexibility and transparency, a user is able to run a dynamic/normal
distributed application anywhere with optimised execution performance, without managing distributed
resources. Based on the standalone model, the thesis further introduces a federated resource negotiation
framework as a step forward towards an autonomous multi-user distributed computing world
glogin - Interactive Connectivity for the Grid
Todays computational grids are used mostly for batch processing and throughput computing, where jobs are submitted to a queue, processed, and finally delivered for post-mortem analysis. The glogin tool provides a novel approach for grid applications, where interactive connections are required. With the solution implemented in glogin, users are able to utilize the grid for interactive applications much in the same way as on standard workstations. This opens a series of new possibilities for next generation grid software. Keywords: grid computing, interactivity 1