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Inria / Raweb 2003
Project: PARIS

Project : paris

Section: Overall Objectives


Middleware systems for computational grids

Computational grids are very powerful machines as they aggregate huge computational resources. A lot of work has been carried out with respect to grid resource management. Existing grid middleware systems focus a lot on resources management like discovery, registration, security, scheduling, etc. However, they provides very few support for grid-oriented programming model.

A suitable grid programming model should be able to take into account the dual nature of a computational grid which is a distributed set of (mainly) parallel resources. Our general objective is to propose such a programming model and to provide adequate middleware systems. Distributed object or component models seems to be a pertinent solution. However, they need to be tailored for scientific applications, in particular with respect of the encapsulation of parallel codes into objects or components, the communications between ``parallel'' objects or components, the required runtime support, the deployment and the adaptability.

The first issue is the relationship between object or component models, which should handle the distributed nature of grid, and the parallelism of computational code, which should take into account the parallelism of resources. It is thus required to efficiently combine both world into a coherent one.

The second issue concerns the simplicity and the scalability of communications between parallel codes. As the available bandwidth is larger than what a single resource could consume, parallel communication flows should allow a more efficient utilization of network resources. Advanced control flow should be used not to congest networks. A crucial aspect of this issue is the support for data redistribution which should be involved in the communication between parallel codes.

Promoting a programming model that simultaneously supports distributed as well as parallel middleware systems, independently of the actual resources, raises three new issues. First, middleware systems should be decoupled from the actual networks so as to be deployed on any kind of network. Second, several middleware systems should be simultaneously active within a same process. Third, solutions to the two previous issues should support high performance constraints to be accepted by users.

The deployment of applications is another issue. Not only, it is important to constrain the deployment by specifying the requirement in term of the computational resource (Gflop/s, amount of memory, etc.), but it is also crucial to specify the constraints related to communication resources such as the amount of bandwidth or the latency between computational resources.

The last issue deals with the dynamic nature of computational grids. As targeted applications may last for very long time, grid environment is expected to change. Not only middleware systems should support adaptability but they should be able to detect variations and should be able to self-adapt. For example, an application may be partially redeployed to take benefit of new resources.


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