Distributed and Parallel Computing (M2 DiPaC)

Apply for the degree
  • Places available
    20
  • Language(s) of instruction
    English
  • Enrolment type
    Formation initiale
  • Type of teaching
    En présentiel
  • Start of programme (indicative date)
Présentation
Objectives

Computer systems are evolving toward higher efficiency and richer functionality across three major, interconnected scientific fields:

  • Distributed systems deliver connectivity and dependable operation across the Internet, clouds, clusters, and sensors, addressing hard problems in synchronization, security, concurrency, and robustness.
  • High-performance and parallel computing (HPC) tackles intensive workloads in science and AI by exploiting supercomputing architectures and rigorous performance engineering.
  • Quantum computing provides algorithms and hardware that exploit quantum parallelism to achieve gains unreachable by classical paradigms.

Building on the foundations that M1 DiPaQ establishes in HPC, distributed systems, and quantum computing, M2 DiPaC specializes on advanced topics in HPC and distributed algorithms for large-scale systems. Students learn to design fast, scalable, and robust solutions for applications in AI, big data analytics, scientific simulations, and quantum-enabled workflows. Students have the opportunity to specialize either in high performance data analysis (HPDA) or hybrid HPC/quantum computing (HQI) through elective courses.

Knowledge objectives:

  • Parallel programming models and performance engineering on modern supercomputers and accelerators.
  • Large-scale distributed algorithms and systems: replication, consensus, consistency, mobile agents, and nature-inspired algorithms with robustness and performance guarantees.
  • Big data analysis, machine learning, and AI algorithms with massive computational challenges (HPDA)
  • Quantum algorithms and simulation using both classical/HPC or quantum workflows (HQI)

Skill objectives:

  • Building high-quality parallel and distributed algorithms and software that meet latency, throughput, and performance targets on target HPC architectures.
  • Developing and analyzing scalable, robust algorithms with theoretical guarantees on scalability, consensus, termination, and fault tolerance.
  • Optimizing HPC code across the stack: complexity, memory locality, vectorization, accelerator use, communication, I/O, and networks.

Resources and practice:

  • Access to university clusters and partner supercomputers for hands-on labs, course projects, code development, and tuning.
  • Use of open-source toolchains and libraries widely adopted by the HPC community.
  • Acquiring modern HPC software engineering practices with advanced C++, IDEs, version control (git), documentation, and continuous integration.
Skills

  • Be able to read and understand research articles in the fields of distributed, parallel and quantum computing.

    • Overall organisation

    The curriculum includes seven core disciplinary courses in high performance, parallel, and distributed computing. In addition, students choose two elective courses to further specialize either in high performance data analysis and AI (HPDA) or in hybrid high performance/quantum computing (HQI). In addition, one soft-skill course from the university catalog reinforces transferable professional skills that support their long-term career development. A mandatory 6 month internship on M2 DiPaC-related themes completes the program.

    The program’s official language is English; all courses take place and course materials are provided in English. Most of our faculty are also fluent in French; hence interaction in French is possible in the courses and assignments (homework, exams, etc.) if needed.

    The program is closely integrated within the Paris-Saclay ecosystem of research laboratories and industrial partners.

    Career prospects

    With the rise of the Cloud, the IoT, the constant development of supercomputers, the deployment of the European quantum flagship and the national quantum plan, the QDCS Master's program is targeting blossoming scientific and economic fields. The Master enables students to continue with a PhD, by preparing a thesis within a public research organization or the R&D department of a large company. The Master also enables students to easily integrate the industrial world, for example within companies having high computing needs, or more generally in the high-tech world, whether in the R&D departments of large companies or in startups developing cutting-edge software.

    Course Prerequisites
    • Audience. M2 DiPaC is the natural continuation of M1 DiPaQ for students aiming to specialize in advanced high-performance, parallel, and distributed computing.
    • Prerequisites. Strong computer science background with basics in parallel programming and distributed systems. Solid mathematics (especially linear algebra) and programming skills are expected.
    • Admissions from other related tracks. Outstanding students from related master tracks can be admitted if they already have some fundamentals in parallel or distributed computing. If needed, they will be allowed to take selected M1 DiPaQ courses as electives to close gaps.
    • Double-degree pathway. We routinely admit exceptional engineering students finishing their fourth year (M1 equivalent) at nearby Paris-Saclay schools (CentraleSupélec, Polytech Paris-Saclay, ENSTA Paris, ...) as double-degree students, who desire to complete their fifth year at the engineering school in parallel with M2 DiPaC. A dedicated arrangement between two programs allows to study in both, with possible course waivers subject to approval by the master’s coordinators on each side. If you plan to apply, please contact the M2 DiPaC coordinator and your academic coordinator at the engineering school in advance.
    • Positioning with respect to M2 QMI. While M2 DiPaC offers some optional quantum computing courses aligned with classical/HPC workflows, applicants seeking an exclusive focus on advanced quantum information science are encouraged to apply to our partner program M2 QMI.

    A limited number of scholarships (Eiffel, IDEX, Quantum Saclay) are available for exceptional candidates.

    Rythme de la formation
    The **academic year** is organized in **four trimesters**. All **courses** are taught during the **first three trimesters**, and the **mandatory 6-month internship** spans the **fourth trimester and the summer period**. _L’**année universitaire** est organisée en **quatre trimestres**. Tous les **cours** ont lieu pendant les **trois premiers trimestres**, et le **stage obligatoire de 6 mois** se déroule au **quatrième trimestre et durant la période estivale**._
    Internships and supervised projects

    Starting in the fourth trimester, M2 DiPaC involves a mandatory 6 month internship. The internship addresses the program themes—high-performance, parallel, and distributed computing—or one of two specializations (HPC for AI & big data analysis (HPDA) or Hybrid HPC/quantum computing (HQI)), and is hosted by a research lab or an industry team within a company (engineering or R&D). In the end, students submit a written report and present their work during the internship defenses for evaluation.

    Transfer paths

    Oui

    Post-graduate profile

    During the M2 QDCS, students will acquire solid knowledge of the fields of distributed algorithms, parallel computing, quantum computing, but also strong skills in advanced programming, especially for HPC (MPI, OpenMP, etc.). The choice of optional modules will allow them to become familiar with various possible fields of application, such as AI, data sciences or security. It is therefore a broad and complete training course that allows them to both acquire solid theoretical foundations and master their practical implementation. Thus, the course enables rapid integration into the industrial and scientific worlds, by developing the ability to anticipate technological developments.

    Location
    ORSAY
    GIF SUR YVETTE
    Tuition fees

    Find out more about the registration fees

    Collaboration(s)
    Academic partner

    École Polytechnique

    Télécom Paris

    INRIA

    Sorbonne Université

    Université de Paris

    Technion - Israel Institute of Technology

    University of Tennessee

    Old Dominion University

    École Polytechnique Fédérale de Lausanne

    Lisbon University

    Karlsruhe Institute of Technology

    University of Vienna

    Laboratories

    Formal Methods Laboratory (LMF)
    Interdisciplinary Laboratory of Digital Sciences (LISN)
    Computer Science Laboratory of the École polytechnique (LIX)
    Information Processing and Communication Laboratory (LTCI)
    Signals and Systems Laboratory (I2S)

    Programme

    The schedule will be posted shortly.

    Modalités de candidatures
    Application period
    From 15/04/2026 to 30/05/2026
    Admission criteria
    Dossier
    Compulsory supporting documents

    • Motivation letter.

      (A letter detailing the motivation and reasons for willing to study parallel and distributed computing in the M2 DiPaC master's program in the light of previous studies and experiences as well as future career plans.)

    • All transcripts of the years / semesters validated since the high school diploma at the date of application.

      (Grades of all courses since high school.)

    • Curriculum Vitae.

      (A CV detailing all previous studies, internships, trainings, work experience (if any), distinctions and awards, as well as other personal interests and activities.)
    Additional supporting documents

    • Copy diplomas.

    • Letter of recommendation or internship evaluation.

    • Document at your convenience.

    • VAP file (obligatory for all persons requesting a valuation of the assets to enter the diploma).

      (only needed in case you have officially validated your prior professional experience to count as equivalent to a university degree)

    • Supporting documents :
      - Residence permit stating the country of residence of the first country
      - Or receipt of request stating the country of first asylum
      - Or document from the UNHCR granting refugee status
      - Or receipt of refugee status request delivered in France
      - Or residence permit stating the refugee status delivered in France
      - Or document stating subsidiary protection in France or abroad
      - Or document stating temporary protection in France or abroad.

    Contact(s)
    Course manager(s)
    Janna BURMAN - janna.burman@lri.fr
    Oguz KAYA - oguz.kaya@universite-paris-saclay.fr
    Administrative office
    Eva PERIN - eva.perin@universite-paris-saclay.fr