Postdoc: Open System-Level Framework for AI Architectures

ecolecentraledelyon

Écully

Hybride

EUR 40 000 - 56 000

Plein temps

Il y a 12 jours
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Résumé du poste

Emerging computing technologies research at INL, Ecole Centrale de Lyon, Écully, France, seeks a postdoctoral researcher to build a modular evaluation framework for design space exploration and system-design-technology co-optimization of future AI accelerators. The role spans computer architecture, accelerator design, performance modelling and hardware-software co-design.

You will convert device-level results into parametrized models and enable bottom-up and top-down constraint propagation to

Qualifications

  • PhD in Electrical/Electronic Engineering, Computer Engineering, Computer Science or related discipline with strong research background.
  • Strong Python programming skills and software engineering practice.

Responsabilités

  • Develop an open, modular, extensible system-level evaluation framework for design space exploration (DSE) and SDTCO of emerging computing architectures.
  • Convert low-level results into parameterized architectural models for efficient exploration of accelerators for AI workloads.
  • Expose cross-layer trade-offs, bottlenecks, and feasible breaking points with top-down constraint propagation.
  • Collaborate with INL Electronics group to ensure reproducibility, openness, and reuse of components.

Connaissances

Python
C/C++
RISCV
PyTorch

Formation

PhD in Electrical/Electronic Eng

Outils

SystemC
QEMU
Timeloop
NeuroSim
CiMLoop/AccelForge

Description du poste

Emerging computing technologies research at INL, Ecole Centrale de Lyon, Écully, France, seeks a postdoctoral researcher to build a modular evaluation framework for design space exploration and system-design-technology co-optimization of future AI accelerators. The role spans computer architecture, accelerator design, performance modelling and hardware-software co-design.

You will convert device-level results into parametrized models and enable bottom-up and top-down constraint propagation to

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