Engineer F/M. MLIR based Compiler optimization framework for deep learning workloads

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Type de contrat : CDD

Contrat renouvelable : Oui

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Ingénieur scientifique contractuel

A propos du centre ou de la direction fonctionnelle

The Centre Inria de l’Université de Grenoble groups together almost 600 people in 24 research teams and 9 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, …), but also with key economic players in the area.

The Centre Inria de l’Université Grenoble Alpes is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

 

 

Contexte et atouts du poste

CORSE is a joint research group in the LIG laboratory that regroups several expertise that stand at the interface between software and hardware: those are domain specific application/library tuning, compiler optimization, run-time systems, and debugging/monitoring. Our domains of application include performance (both speed and energy consumption), reliability, and teaching of computer science. An important activity concerns the optimization of machine learning applications for specific high-performance embedded architectures.

The position is funded by the DeepGreen project. The goal of CORSE in this project is to advance research in compiler optimization, including compiler infrastructure and scheduling heuristics, specifically for deep learning codes.

Mission confiée

The aim of the position is to contribute to the development of tools that help the programmer to obtain highly optimized code of deep learning applications. This work may includes various tasks:

  • Infrastructure:
    • Metaprogramming: Enrich high and low-level MLIR transform dialects with optimizing loop and hyper-block transformations
    • Traditional design: Extended MLIR with backend passes
  • Language: Implementation of programers-level primitives which describe the "schedule"
  • Code generation: Handle specific cases such as low-level code for sparse operators and/or data-movement/packing for distributed storage systems.

The targeted architectures are CPU-like tensor computation accelerators.

Principales activités

The main activities include:

  • Contributions to MLIR-based compiler infrastructure
  • Development of code generators (compute & data-movement)
  • Technical support to PhD students

Compétences

The position requires:

  1. Development experience with MLIR
  2. Background in compiler infrastructures for deep-learning applications
  3. Expertise in compiler optimization focusing on data locality and parallelism (including data dependencies, tiling, etc.)
  4. Proficiency in C, C++, and Python programming
  5. Strong communication skills (teamwork) and the ability to thrive in a research environment with flexible development directives
 

Avantages

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (90 days / year) and flexible organization of working hours
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage under conditions

Rémunération

Gross salary : from 2 692 euros before deduction of tax incomes depending on laboral experiences and degrees.