PhD position

Applications should be submitted online on the dedicated website. For more information, please contact François Tessier, researcher at INRIA Rennes – Bretagne Atlantique Research Center and IRISA (CNRS/Université de Rennes), [email protected].

 

 

 

 

Context

Launched in 2023 for a duration of 6 years, The NumPEx PEPR aims to contribute to the design and development of numerical methods and software components that will equip future European Exascale and post-Exascale machines. NumPEx also aims to support scientific and industrial applications in fully exploiting their potentials.

Exa-MA aims to revolutionize methods and algorithms for exascale scaling: discretization, resolution, learning and order reduction, inverse problem, optimization and uncertainties. We are contributing to the software stack of future European computers.

 

Mission

The KerData team is a small team of 8 scientists and 5 PhD students who’s leading multiple projects and international collaborations. The team is dedicated in experimental research, validated by implementation and experimentation of software prototypes with real-word applications.

Dealing with this high degree of storage heterogeneity is a real challenge for scientific workflows and applications. This PhD thesis proposes to model and simulate heterogeneous storage systems in order to study their behavior, predict their performance and propose innovative algorithmic approaches for better resource utilization.

Main activities

One of the aims of this thesis is to make better use of storage resources for scientific applications and workflows that are destined to run on Exascale supercomputers. Initially, storage systems such as Lustre and DAOS will be studied, modeled and simulated in an existing WRENCH-based simulator, called StorAlloc, developed in the team. This study will shed light on the criteria influencing the performance of these systems. Secondly, advanced resource allocation algorithms will be proposed, implemented and evaluated in the simulator to overcome the limitations of existing methods (e.g. Lustre uses the disks of its storage system in a simple round-robin manner). Multiple criteria can be taken into account in those algorithms such as contention or energy. Tools developed by the CEA, including the Robinhood policy engine and the outcomes from the IO-SEA European Project will also be used to validate these contributions on real systems. For this work, a strong emphasis will be put on international collaborations, especially with the University of Manoa (HI, USA), and on national partnership such as with the French SKA team providing a relevant use-case for this work. The candidate will also have the opportunity to be hosted for 3-6 month internships abroad to strengthen the international visibility of his/her work and benefit from the expertise of other researchers in the field.

Required skills

  • An excellent Master degree in computer science or equivalent
  • Completion of a teaching unit in high-performance computing or distributed computing is an advantage
  • Programming skills in C/C++ and Python
  • Good communication skills in oral and written English.
  • Open-mindedness, strong integration skills and team spirit
More information and references