Cea - Commissariat à l'Energie Atomique

<h2><strong>Description du poste</strong></h2>
<h3><strong>Domaine</strong></h3>
<p>Composants et équipements électroniques</p>
<h3><strong>Contrat</strong></h3>
<p>Stage</p>
<h3><strong>Intitulé de l'offre</strong></h3>
<p>Internship - Combining Analytical and ML-based Models for Efficient HW Performance Prediction-Saclay-H/F</p>
<h3><strong>Sujet de stage</strong></h3>
<p>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.</p>
<p>The Environmental Design and Architecture Laboratory (LECA), within the Digital Systems and Integrated Circuits Department (DSCIN), is a multidisciplinary team specializing in hardware IP design and simulation methodologies, with an expanding research focus on AI-driven Electronic Design Automation (EDA).</p>
<h3><strong>Durée du contrat (en mois)</strong></h3>
<p>6 mois</p>
<h3><strong>Description de l'offre</strong></h3>
<p>As an intern at the CEA, you will have the opportunity to work within a world-renowned research environment. Our teams consist of passionate and dedicated experts, providing an ideal setting for learning and collaboration. You will have access to state-of-the-art equipment and top-tier research resources to carry out your assignments. The work conducted may potentially lead to a scientific publication.</p>
<p><strong>Context :</strong></p>
<p>The goal of this internship is to investigate hybrid performance modeling techniques that combine ML-based data-driven models with structured top-down analytical models. Using the CVA6, CVA6S, CVA6S+ architectural evolution as a case study, the internship will explore:</p>
<p><strong>What do we expect from you?</strong></p>
<ul>
<li><strong>Hybrid modeling:</strong> Combining simulation ML-driven performance insights with analytical architectural models.</li>
<li><strong>Transferability:</strong> Evaluating whether models developed for one hardware generation can be adapted to subsequent generations with limited retraining or recalibration.</li>
<li><strong>Design-space exploration:</strong> Assessing the ability of hybrid models to efficiently predict the impact of architectural modifications.</li>
</ul>
<p>The internship aims to develop and evaluate a hybrid modeling methodology that balances accuracy, expressiveness, and transferability across hardware generations. The ultimate objective is to assess its potential for enabling flexible hardware design-space exploration, reducing reliance on costly cycle-accurate simulations.</p>
<p><strong>References</strong></p>
<p><em>[ISCA'25] Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion</em></p>
<p><em>[ICCAD'23] PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions</em></p>
<p><em>#Cea-List</em></p>
<h3><strong>Profil du candidat</strong></h3>
<p><strong>Profile :</strong></p>
<ul>
<li><strong>Required level:</strong> Master's degree or Engineering diploma</li>
<li><strong>Required Skills:</strong> Familiarity with AI, knowledge of computer architecture, proficiency in Python and C/C++, and experience with Git</li>
<li><strong>Other Qualities:</strong> Collaborative mindset and a genuine curiosity</li>
</ul>
<h2><strong>Localisation du poste</strong></h2>
<h3><strong>Site</strong></h3>
<p>Saclay</p>
<h3><strong>Localisation du poste</strong></h3>
<p>France, Ile-de-France, Essonne (91)</p>
<h3><strong>Ville</strong></h3>
<p>Saclay</p>
<h2><strong>Critères candidat</strong></h2>
<h3><strong>Diplôme préparé</strong></h3>
<p>Bac+5 - Diplôme École d'ingénieurs</p>
<h2><strong>Demandeur</strong></h2>
<h3><strong>Disponibilité du poste</strong></h3>
<p>01/02/2027</p>
<h2><strong>Informations générales</strong></h2>
<h3><strong>Entité de rattachement</strong></h3>
<p>Le CEA est un acteur majeur de la recherche, au service des citoyens, de l'économie et de l'Etat.</p>
<p>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.</p>
<p>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.</p>
<p>Les 20 000 collaboratrices et collaborateurs du CEA partagent trois valeurs fondamentales :</p>
<ul>
<li>La conscience des responsabilités</li>
<li>La coopération</li>
<li>La curiosité</li>
</ul>
<h3><strong>Référence</strong></h3>
<p>2026-42085</p>
<h3><strong>Description de l'unité</strong></h3>
<p>Within the CEA List, the Electronics Design Automation and Architectures Laboratory (LECA) has the mission to design innovative and flexible system-on-chip architectures that meet the challenges of performance, cost, energy consumption, safety and security, targeting critical embedded systems and HW accelerators for embedded AI. To reduce the development time and improve the quality of these architectures, the team of experts develop innovative design tools and methods.</p>


Internship - Combining Analytical and ML-based Models for Efficient HW Performance Prediction-Saclay-H/F

Internship - Combining Analytical and ML-based Models for Efficient HW Performance Prediction-Saclay-H/F

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