Team AlGorille

Overall Objectives
Scientific Foundations
Application Domains
New Results
Other Grants and Activities

Section: Application Domains

Providing Environments for Experiments

Participants : Sylvain Contassot-Vivier, Fekari El Medhi, Jens Gustedt, Emmanuel Jeannot, Lucas Nussbaum, Martin Quinson, Philippe Robert, Cristian Rosa, Stéphane Vialle.

Simulating Grid Platforms

We participate in the development of the SimG rid tool. It enables the simulation of distributed applications in distributed computing environments for the specific purpose of developing and evaluating scheduling algorithms. Simulations not only allow repeatable results (what is hard to achieve on shared resources) but also make it possible to explore wide ranges of platform and application scenarios. SimG rid implements realistic fluid network models that result in very fast yet precise simulations. SimG rid also enables the simulation of distributed scheduling agents, which has become critical for current scheduling research in large-scale platforms. This is one of the main simulation tools used in the Grid Computing community.

Emulating Heterogeneity

We have designed a tool called Wrekavoc . The goal of Wrekavoc is to define and control the heterogeneity of a given platform by degrading CPU, network or memory capabilities of each node composing this platform. Our current implementation of Wrekavoc has been tested on an homogeneous cluster. We have shown that configuring a set of nodes is very fast. Micro-benchmarks show that we are able to independently degrade CPU, bandwidth and latency to the desired values. Tests on algorithms of the literature (load balancing and matrix multiplication) confirm the previous results and show that Wrekavoc is a suitable tool for developing, studying and comparing algorithms in heterogeneous environments.

Use of Formal Methods to Assess Distributed Algorithms

In joint research with Stephan Merz of the Mosel team of INRIA Nancy and LORIA, we are interested in the verification (essentially via model checking) of distributed and peer-to-peer algorithms. Whereas model checking is now routinely used for concurrent and embedded systems, existing algorithms and tools can rarely be effectively applied for the verification of asynchronous distributed algorithms and systems. Our goal is to adapt these methods to our context.


The Aladdin-G5K initiative is an action funded by INRIA that ensures the sustainability of the Grid'5000 platform.

The purpose of Grid'5000 is to serve as an experimental testbed for research in Grid Computing. In addition to theory, simulators and emulators, there is a strong need for large scale testbeds where real life experimental conditions hold. Grid'5000 aims at building a highly reconfigurable, controllable and monitorable experimental Grid platform gathering nine sites geographically distributed in France featuring a total of five thousands CPUs. We are in charge of one of these nine sites and we currently provide 1216 cores to the community.


Intercell aims at setting up a cluster (256 PCs) for interactive fine grain computation. It is granted by the Lorraine Region (CPER 2007), and managed at the Metz campus of SUPÉLEC.

The purpose is to allow easy fine grain parallel design, providing interactive tools for the visualization and the management of the execution (debug, step by step, etc ). The parallelization effort is not visible to the user, since InterCell relies on the dedicated parXXL framework, see  5.1 below. Among the applications that will be tested is the interactive simulation of PDEs in physics, based on the Escapade project, see [4] .

Experimental platform of GPU clusters

We participate in the scientific exploitation of two experimental 16-node clusters of GPUs that are installed at the SUPÉLEC Metz site. This platform allows to experiment scientific programming on GPU ("GPGPU"), and to track computing and energetic performances, with specific monitoring hardware. Development environments available on these GPU clusters are mainly the gcc suite and its OpenMP library, OpenMPI and the CUDA environment of nVIDIA's nvcc compiler.


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