Exploring the Generalizability of ML-driven Performance Model Generation for HW Design H/F

Détail de l'offre

Informations générales

Entité de rattachement

Le CEA est un acteur majeur de la recherche, au service des citoyens, de l'économie et de l'Etat.

Il apporte des solutions concrètes à leurs besoins dans quatre domaines principaux : transition énergétique, transition numérique, technologies pour la médecine du futur, défense et sécurité sur un socle de recherche fondamentale. Le CEA s'engage depuis plus de 75 ans au service de la souveraineté scientifique, technologique et industrielle de la France et de l'Europe pour un présent et un avenir mieux maîtrisés et plus sûrs.

Implanté au cœur des territoires équipés de très grandes infrastructures de recherche, le CEA dispose d'un large éventail de partenaires académiques et industriels en France, en Europe et à l'international.

Les 20 000 collaboratrices et collaborateurs du CEA partagent trois valeurs fondamentales :

• La conscience des responsabilités
• La coopération
• La curiosité
  

Référence

2024-33918  

Description de l'unité

The French Atomic Energy and Alternative Energies Commission (CEA) is a major player in research, development and innovation. This technological research organization is active in three main areas: energy, information and health technologies, and defense. Recognized as an expert in its fields, CEA is fully integrated into the European research area and is expanding its presence internationally. The Laboratory for Systems and Technology Integration (LIST), located in the southern Île-de-France region (Saclay), has the mission of contributing to technology transfer and promoting innovation in the field of parallel computing systems.

Description du poste

Domaine

Composants et équipements électroniques

Contrat

Stage

Intitulé de l'offre

Exploring the Generalizability of ML-driven Performance Model Generation for HW Design H/F

Sujet de stage

This internship provides a valuable opportunity to gain hands-on experience with machine learning techniques for model generation and HW/SW co-design, contributing to innovative approaches in EDA (Electronic Design Automation).

Durée du contrat (en mois)

5 à 7 mois

Description de l'offre

The Environmental Design and Architecture Laboratory (LECA), within the Digital Systems and Integrated Circuits Department (DSCIN), is a multidisciplinary technological research team comprising experts in hardware IP design and simulation tools. A key contribution of the Lab lies in its innovative methodologies and tools for automating model generation through machine learning techniques. In particular, the kMLeon tool facilitates the automatic generation of extra-functional models, such as performance and power ones.

 

The internship is associated with the TRISTAN European project [1], which aims to strengthen the European RISC-V ecosystem. It build upon ongoing work on automated performance model generation from RTL simulations using kMLeon, specifically for the CVA6 HW design of the OpenHWGroup [2]. The resulting models integrate with the QEMU emulator, enabling accurate performance estimations for various workloads while maintaining high simulation speed [3].

 

The intern will explore and extend the generalizability of this methodology along both SW and HW dimensions. On the SW side, RTL simulations are often compute-intensive due to large workloads, making data reduction essential to accelerate training data generation and model development. To address this, the intern will develop an innovative automated data reduction to optimize the process before RTL simulation. On the HW side, model generation has so far targeted single HW configurations. The intern will develop an innovative methodology to expand the model generation process to account for architectural variations, allowing for thorough design space exploration.

 

[1] https://tristan-project.eu

[2] https://github.com/openhwgroup/cva6

[3] https://riscv-europe.org/summit/2024/media/proceedings/posters/170_poster.pptx

Profil du candidat

  • Required Level: Master's degree or Engineering diploma
  • Duration: 6 months
  • Skills Required: Familiarity with AI, knowledge of Computer Architecture, proficiency in Python and C/C++, and experience with Git
  • Other Qualities: Strong command of English, collaborative mindset, and a genuine curiosity
  • Application Materials: Please submit a CV together with academic transcripts and a cover letter

In line with CEA's commitment to integrating people with disabilities, this job is open to all.

Localisation du poste

Site

Saclay

Localisation du poste

France, Ile-de-France, Essonne (91)

Ville

  Palaiseau