2019-01313 - Post-Doctoral Research Visit F/M Design of the scientific libray that implements block Krylov subspace mehtod for the solution of large linear systems and eigenprobkems

Contract type : Public service fixed-term contract

Renewable contract : Oui

Level of qualifications required : PhD or equivalent

Other valued qualifications : Formation initiale d'ingénieur en calcul scientifique

Fonction : Post-Doctoral Research Visit

About the research centre or Inria department

An important force which has continued to drive HPC has been to focus on frontier milestones which consist in technical goals that symbolize the next stage of progress in the field. After the step of the teraflop machine in the 1990s, the HPC community envision the use of generalist petaflop supercomputers and soon coming exaflop machines in the 2020s. For application codes to sustain petaflop and more using a few millions of cores or more will be needed, regardless of processor technology. Currently, a few HPC simulation codes easily scale to this regime and major code development efforts are critical to achieve the potential of these new systems. Scaling to at this rate will involve improving physical models, mathematical modelling, super scalable algorithms that will require paying particular attention to acquisition, management and vizualization of huge amounts of scientific data.

In this context, the purpose of the HiePACS project is to perform efficiently frontier simulations arising from challenging research and industrial multiscale applications. The solution of these challenging problems require a multidisciplinary approach involving applied mathematics, computational and computer sciences. In applied mathematics, it essentially involves advanced numerical schemes. In computational science, it involves massively parallel computing and the design of highly scalable algorithms and codes to be executed on future petaflop (and beyond) platforms. Through this approach, HiePACS intends to contribute to all steps that go from the design of new high-performance more scalable, robust and more accurate numerical schemes to the optimized implementations of the associated algorithms and codes on very high performance supercomputers.

Context

This work will be carried out within the HiePACS team, which specializes in the design and implementation of high-performance software packages for large scale numerical simulations. Integration and validation will be carried out in collaboration with partner teams and the scalability will be studied via access to platforms in France and Europe. This mission will be carried out within the framework of a European project H2020 entitled PRACE-6IP.


Assignment

For many years, the team has been developing important algorithmic know-how for high-performance computing in libraries such as Fabulous (https://gitlab.inria.fr/solverstack/fabulous) for solving linear systems with multiple second members. These solvers have enabled our users to effectively solve linear systems of equations from applications for real 3D cases for parametric or inversion studies on a large number of processors.

The main tasks are application-oriented:

  • In collaboration with a team from LRZ (Munich) and Computation-based Science and Technology Research Center (CaSToRC) of The Cyprus Institute, partners of the European project, participate in the definition of flexible APIs and the integration of the library into major application codes of the project. Study the scaling up, identify possible bottlenecks and propose possible remedies.
  • Contribute to the development and integration of new numerical methods to improve the numerical behaviour of these solvers while reducing their memory and calculation costs

Main activities

  • Study and development of parallel linear solvers
  • Collaborations with the development teams to identify possible performance  performance
  • Participation in project progress meetings and writing of deliverables

Skills

PhD in computational science (applied mathematics, scientific computation or computer science).


High-performance computing and algorithms; parallel and distributed programming; numerical linear algebra; C++; MPI

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Remuneration

2653€ gross monthly