Section: New Results

Cooperative Resource Managers

Participants : Eddy Caron, Cristian Klein, Christian Pérez, Noua Toukourou.

Integration of SALOME with CooRM

We have continued the validation works of the CooRM RMS architecture  [52] . To this end, we focused on the SALOME numerical simulation platform developed and used jointly by EDF and CEA. In 2012, we have mostly started the integration of CooRMv1 concepts in SALOME. CooRMv1 targets moldable applications and allows them to efficiently employ their custom resource selection algorithms. We have done the necessary changes in SALOME, thus obtaining a working prototype implementation. Thanks to this, SALOME applications could be published with a custom launcher (implementing a resource selection algorithm) so as to transparently launch applications efficiently, instead of having to leave this burden to the user.

A Distributed Resource Management Architecture for Moldable Applications

In 2011, we have proposed CooRMv1  [52] , a centralized RMS architecture to efficiently support moldable applications. Having a centralized architecture is however undesirable for geographically-distributed resources such as Grids or multiple Clouds. For example, if there is a network failure, some users will not be able to access any resources, not even those that are located on their side of the bisection.

To this end, we extended CooRMv1 and proposed a distributed version of it, distCooRM, in collaboration with the Myriads team. It allows moldable applications to efficiently co-allocated resource managed by independent agents. Simulation results show that the approach is feasible and scales well for a reasonable number of applications. In other words, it presents good strong scalability, but not weak scalability, which we intend to address in future work.

A Resource Management Architecture for Fair Scheduling of Optional Computations

In collaboration with two teams from IRIT, we have identified a use-case that is currently badly supported. Some applications, such as Monte-Carlo simulations, contain optional computations: These are not critical, but completing them would improve the results. When executing these application on HPC resources, most resource managers, such as batch schedulers, require the user to submit a predefined number of computing requests. If the user submits too many requests, the platform might become overloaded, whereas if the user submits too few requests, then resources might be left idle.

To solve this issue, we proposed a resource management architecture, called Diet -ethic [42] , which auto-tunes the number of optional requests. It improves user happiness, fairness and the number of completed requests, when compared to a system which does not support optional computations.