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Section: Partnerships and Cooperations
International Initiatives
Inria International Labs
North America
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JLESC (former JLPC) (Joint Laboratory for Extreme-Scale Computing) with University of University of Illinois Urbana Champaign, Argonne Nat. Lab and BSC. Several members of MESCAL are partners of this laboratory, and have done several visits to Urbana-Champaign or NCSA.
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Associated Team with Berkeley. MESCAL is thus involved in the Inria@SiliconValley program.
Inria Associate Teams
EXASE
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International Partner (Institution - Laboratory - Researcher):
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See also: https://team.inria.fr/exase/
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The main scientific goal of this collaboration for the three years is the development of state-of- the-art energy-aware scheduling algorithms for exascale systems. Three complementary research directions have been identified : (1) Fundamentals for the scaling of schedulers: develop new scheduling algorithms for extreme exascale machines and use existing workloads to validate the proposed scheduling algorithms (2) Design of schedulers for large-scale infrastructures : propose energy-aware schedulers in large-scale infrastructures and develop adaptive scheduling algorithms for exascale machines (3) Tools for the analysis of large scale schedulers : develop aggregation methodologies for scheduler analysis to propose synthetized visualizations for large traces analysis and then analyze schedulers and energy traces for correlation analysis
CLOUDSHARE
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Title: Guaranteed Application Performance on Idle Data Center Resources
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International Partner (Institution - Laboratory - Researcher):
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See also: http://mescal.imag.fr/membres/derrick.kondo/ea/ea.html
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Data centers are often 85% idle as they must over-provision to ensure service level agreements. At the same time, high data center utilization is essential for efficient resource usage and optimal revenue. One way to improve utilization is for low-priority applications to use the idle resources of data centers, allowing high-priority applications to preempt them at any time. While users benefit from the lower costs of using these idle resources, parallel applications such as Map-Reduce can suffer severe overheads and unpredictable performance due to unexpected preemption and unavailability. The goal of this project is to enable complex applications to utilize idle data center resources with guaranteed performance. Our approach will be as follows. First, we will investigate novel statistical methods to predict the execution time of complex batch applications. Second, we will apply machine learning methods to predict idleness in data centers. Third, we will craft fair scheduling algorithms for multiple applications that compete for idle data center resources. The collaboration bridges experts in statistical modeling and simulation from the Inria MESCAL team with system and scheduling experts in the Berkeley BOINC team and the Google Infrastructure team.
Inria International Partners
Declared Inria International Partners
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MESCAL has strong connections with both UFRGS (Porto Alegre, Brazil) and USP (Sao Paulo, Brazil). The creation of the LICIA common laboratory (see next section) has made this collaboration even tighter.
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MESCAL has strong bounds with the University of Illinois Urbana Champaign, within the (Joint Laboratory on Petascale Computing, see previous section).
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MESCAL also has long lasting collaborations with University of California in Berkeley.
Participation In other International Programs
South America
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LICIA. The CNRS, Inria, the Universities of Grenoble, Grenoble INP and Universidade Federal do Rio Grande do Sul have created the LICIA (Laboratoire International de Calcul intensif et d'Informatique Ambiante). Jean-Marc Vincent is the director of the laboratory, on the French side.
The main themes are high performance computing, language processing, information representation, interfaces and visualization as well as distributed systems.
More information can be found at http://www.inf.ufrgs.br/licia/ .