Section: Partnerships and Cooperations

International Initiatives

Inria International Labs

• JLESC (Joint Laboratory on Exascale Computing)

  The CORSE team is involved in the JLESC with collaborations with UIUC (Sanjay Kalé) and BSC (Mont-Blanc projects). Kevin Pouget, Brice Videau and Jean-François Méhaut attended to the two JLESC workshops (Barcelona and Bonn) in 2015.

  • Energy Efficiency and Load Balancing

  • The power consumption of High Performance Computing (HPC) systems is an increasing concern as large-scale systems grow in size and, consequently, consume more energy. In response to this challenge, we propose new energy-aware load balancers that aim at reducing the energy consumption of parallel platforms running imbalanced scientific applications without degrading their performance. Our research explores dynamic load balancing, low power manycore platforms and DVFS techniques in order to reduce power consumption.

  • We propose the improvement of the performance and scalability of parallel seismic wave models through dynamic load balancing. These models suffer from load imbalance for two reasons. First, they add a specific numerical condition at the borders of the domain, in order to absorb the outgoing energy. The decomposition of the domain into a grid of subdomains, which are distributed among tasks, creates load differences between the tasks that simulate the borders and those responsible for the central subdomains. Second, the propagation of waves in the simulated area changes the workload on the subdomains on different time-steps. Therefore causing dynamic load imbalance. In order to evaluate the use of dynamic load balancing, we ported a seismic wave simulator to Adaptive MPI, to benefit from its load balancing framework. Our experimental results show that dynamic load balancers can adapt to load variations during the application’s execution and improve performance by 36%.

  • we also focus on reducing the energy consumption of imbalanced applications through a combination of load balancing and Dynamic Voltage and Frequency Scaling (DVFS). Our strategy employs an Energy Daemon Tool to gather power information and a load balancing module that benefits from the load balancing framework available in the CHARM++ runtime system. We propose two variants of our energy-aware load balancer (ENERGYLB) to save energy on imbalanced workloads without considerably impacting the overall system performance. The first one, called Fine- Grained EnergyLB (FG-ENERGYLB), is suitable for plat- forms composed of few tens of cores that allow per-core DVFS. The second one, called Coarse-Grained EnergyLB (CG-ENERGLB) is suitable for current HPC platforms composed of several multi-core processors that feature per-chip DVFS.

• LIRIMA (IDASCO team)

  • The general objective of IDASCO project team is to develop models and tools that can be used to collect the huge amount of data produced by complex computational, biological, epidemiological or environmental systems, and extract knowledge from these data in order to better understand their structure and dynamics for decision making. From 2010 to 2015, the IDASCO activities were focused on the following main thematics : programming environments for parallel execution, parallel algorithms for datamining, social network analysis and trace mining. Some work on wireless sensor networks and geographic information systems with application to sustainable management of natural resources have also been developed. Ten PhD Theses were defended during this period with eight on them co-supervised. There were some industrial collaborations with a brewery company (SABC) on e-Learning platforms and with ORANGE Labs on online registration platforms. These collaborations were done in partnership of the ALOCO project team. The EPICAM project was also developed in partnership with MEDES France, Centre Pasteur Cameroun and the National Program for Fight against Tuberculosis.

  • Jean-François Méhaut is co-director with Maurice Tchuenté of the IDASCO team.

  • Thomas Messi Nguelé is currently preparing a PhD with the coadvising of Maurice Tchuenté. His research work is also part of the IDASCO team.

  • Ylies Falcone and Jean-François Méhaut spent two weeks in Cameroon (Yaoundé) in the context of LIRIMA and CETIC (African Center of Excellence for IT, http://www.cetic.cm/ ).

Inria Associate Teams not involved in an Inria International Labs

IOComplexity

• Title: Automatic characterization of data movement complexity

• International Partner (Institution - Laboratory - Researcher):

  • Ohio State University (United States) - P. Sadayappan

• Start year: 2015

• See also: https://team.inria.fr/corse/iocomplexity/

• The goal of this project is to develop new techniques and tools for the automatic characterization of the data movement complexity of an application. The expected contributions are both theoretical and practical, with the ambition of providing a fully automated approach to I/O complexity characterization, in starking contrast with all known previous work that are stricly limited to pen-and-paper analysis.

  I/O complexity becomes a critical factor due in large part to the increasing dominance of data movement over computation in energy consumption for current and emerging architectures. This project aims at enabling: 1. the selection of algorithms according to this new criteria (as opposed to the criteria on arithmetic complexity that has been used up to now); 2. the design of specific architectures in terms of cache size, memory bandwidth, GFlops etc. based on application-specific bounds on memory traffic; 3. higher quality feedback to the user, the compiler, or the run-time system about data traffic, a major performance and energy factor.

PROSPIEL

• Title: Profiling and specialization for locality

• International Partner (Institution - Laboratory - Researcher):

  • Universidade Federal de Minas Gerais (Brazil) - Computer Science Department - Fernando Magno Quintão Pereira

• Start year: 2015

• See also: https://team.inria.fr/alf/prospiel/

• The PROSPIEL project aims at optimizing parallel applications for high performance on new throughput-oriented architectures: GPUs and many-core processors. Traditionally, code optimization is driven by a program analysis performed either statically at compile-time, or dynamically at run-time. Static program analysis is fully reliable but often over-conservative. Dynamic analysis provides more accurate data, but faces strong execution time constraints and does not provide any guarantee. By combining profiling-guided specialization of parallel programs with runtime checks for correctness, PROSPIEL seeks to capture the advantages of both static analysis and dynamic analysis. The project relies on the polytope model, a mathematical representation for parallel loops, as a theoretical foundation. It focuses on analyzing and optimizing performance aspects that become increasingly critical on modern parallel computer architectures: locality and regularity.

Exase

• Title: Exascale Computing Scheduling Energy

• See also: https://team.inria.fr/exase/

• Inria leader: Jean-Marc Vincent (Mescal)

• Inria teams: Mescal, Moais, Corse

• Corse participants: Jean-François Méhaut, François Broquedis, Frédéric Desprez

• International Partner (Institution - Laboratory - Researcher):

  • Federal University of Rio Grande do Soul (UFRGS, Porto Alegre, Brazil) - Informatics Faculty - L. Schnoor, N. Maillard, P. Navaux

  • Pontifical University Minas (PUC Minas, Belo Horizonte, Brazil) - Computer Science faculty, Henrique Freitas

  • University of Sao Paulo (USP, Sao Paulo, Brazil), IME faculty, Alfredo Goldman

• Start year: 2014

• The main scientific goal of Exase for the three years is the development of state-of- the-art energy-aware scheduling algorithms for exascale systems. As previously stated, issues on energy are fundamental for next generation parallel platforms and all scheduling decisions must be aware of that. Another goal is the development of trace analysis techniques for the behavior analysis of schedulers and the applications running on exascale machines. We list below specific objectives for each development axis presented in the previous section. analysis.

  • Fundamentals for the scaling of schedulers

  • Design of schedulers for large-scale infrastructures

  • Tools for the analysys of large scale schedulers

Participation In other International Programs

• LICIA

• HOSCAR

• EnergySFE (STIC Amsud)