Phd Position F - M Making Caches Predictable Bounded Lifetime Monitoring And Management For Real-Time Systems H/F - INRIA

A propos d'Inria

Inria, l'institut national de recherche dans les sciences et technologies du numérique, est en appui de l'État pour les stratégies nationales de recherche et d'innovation du numérique en tant qu'Agence de programmes. Inria mène plus de 300 projets de recherche et d'innovation avec ses 3500 scientifiques, ingénieurs et personnels d'appui, en partenariat avec les universités et l'écosystème numérique (entreprises, entrepreneurs, acteurs publics). Ensemble, nous explorons des domaines clés comme l'intelligence artificielle, la cybersécurité, l'informatique quantique, le Cloud, la transformation numérique de la santé, les jumeaux numériques ou encore les technologies numériques pour la défense. Nous construisons des solutions concrètes telles que des logiciels, des startups technologiques, des partenariats avec les entreprises du tissu national et des formations de pointe. Notre objectif : l'impact scientifique, technologique et industriel au service de la souveraineté numérique de la France.

PhD Position F/M Making Caches Predictable: Bounded Lifetime Monitoring and Management for Real-Time Systems
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Niveau de diplôme exigé : Bac +5 ou équivalent

Fonction : Doctorant

A propos du centre ou de la direction fonctionnelle

The Inria Centre at Rennes University is one of Inria's nine centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.

Contexte et atouts du poste

The PhD will be led by Inria Rennes, in close collaboration with RPTU and Inria Lille under the ANR PRCI CoCoDaLi

Additional information about the city and the university

Rennes is a vibrant and student-friendly city in northwestern France. The city has a thriving student culture, with plenty of bars, restaurants, cultural events, and an affordable cost of living. Additionally, Rennes is evaluated as one of the best cities to live in Europe.

Rennes is home to the University of Rennes, one of the largest universities in France. The University of Rennes has a strong focus on innovation and technology. It is home to many world-renowned research institutes, including INSA, IRISA, and INRIA Rennes. These institutes offer a wide range of Ph.D. programs in computer science, covering various topics such as artificial intelligence, machine learning, data science, and hardware and software engineering. Ph.D. students in Rennes benefit from close relationships with faculty and access to state-of-the-art facilities. The students also have the opportunity to collaborate with leading researchers worldwide.

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Mission confiée

Context

Caches are one of the main reasons modern processors are fast - and one of the main reasons real-time systems are hard to certify.

In safety-critical domains such as autonomous vehicles, avionics, robotics, industrial control, and cyber-physical systems, software must not only produce the correct result; it must also do so within a guaranteed deadline. To provide such guarantees, engineers need reliable bounds on the Worst-Case Execution Time, WCET, of each task. Yet caches make this difficult: they evict data that will be needed later, and create interference between tasks or even within the same task.

Today, much of this interference is treated pessimistically. Timing analyses often assume worst-case cache behavior because they cannot precisely know which cache blocks are hits or misses. This pessimism leads to overestimated WCET bounds, reduced schedulability, underused hardware resources, and more expensive system designs.

The goal of this PhD is to design mechanisms that turn caches from a source of unpredictability into a resource that can be controlled, reasoned about, and exploited more efficiently in real-time systems.

Principales activités

ResearchActivities

This PhD focuses on the design, analysis, implementation, and evaluation of predictable cache management mechanisms for real-time systems, with the goal of improving execution efficiency while enabling tighter and more reliable WCET bounds.

To achieve that, we will propose low-overhead, bounded, and analyzable mechanisms for monitoring memory block lifetimes and cache management mechanisms to reduce WCET pessimism. We will investigate hardware-assisted and software-assisted mechanisms to monitor the runtime evolution of memory object lifetimes in the cache hierarchy. The monitoring mechanisms must have constant and bounded overhead, independent of the cache state, so that they remain compatible with WCET analysis. We will design runtime cache managementmechanisms that enforce allocation and scheduling decisions, at different granularities. We will evaluate these mechanisms in terms of predictability, implementation complexity, compatibility with memory hierarchies and cache coherence protocols, and performance impact. The PhD will include a systematic analysis of the trade-offs between monitoring granularity, managementgranularity, runtime overhead, WCET pessimism, and system performance.

The research will bridge offline scheduling, cache allocation, and runtime enforcement to improve both predictability and efficiency in real-time systems.

Compétences

Candidate Profile

The candidate should have a strong background in one or more of the following areas:

- computer architecture
- cache and memory hierarchy design
- real-time systems
- operating systems or runtime systems
- WCET analysis

Good programming skills are expected, preferably in C/C++, and Python.

Experience with architectural simulators, such as GEM5, and low-level systems programming would be an advantage.

Languages: proficiency in written English and fluency in spoken English. The interviews for the PhD will be in English.

Relational skills: thecandidatewillworkin a research team, where regular meetings will be set up.The candidatehas to be able to present the progress oftheir work in a clear and detailed manner.

Other values appreciated: Open-mindedness, strong integration skills, and team spirit.

Most importantly, we seek highly motivated candidates.

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 (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

Rémunération

monthly gross salary 2300 euros