Research


I do my research in the Inria team Topal, where I work on improving performance of HPC runtime systems, especially distributed runtime systems. Currently, I focus on how (distributed) runtime systems can help to improve the development and performance of AI applications.

Projects

I am involved in the following projects:

  • NumPEx, especially the Exa-SofT sub-project which aims at adapting the HPC software stack for exascale systems.
  • Cupseli, especially focusing on the optimisation of network communications in geo-distributed AI training.
  • Camelia, which is a project to develop a French accelerator and its software stack, specialized on machine-learing related operations. I co-lead with Gaël Thomas the package about the runtime system.

PhD students

  • Tristan Riehs: Integration of asynchronous network communication scheduling and task scheduling, co-supervised with Samuel Thibault and Alexandre Denis
  • Fares Boudjaoui: Resilient network communications, tolerant to failures and volatility, and suited for artificial intelligence applications , co-supervised with Thomas Herault

Interns

Misc

I did a postdoc in the Research Group Parallel Computing of the Technical University of Vienna, where I worked with Jesper Larsson Träff, Sascha Hunold and Ioannis Vardas on MPI process mapping and estimation of possible performance improvement of MPI applications.

I did my PhD thesis in the TADaaM team in Inria Bordeaux Sud-Ouest, under the supervision of Alexandre Denis and Emmanuel Jeannot.
I worked on interactions between task-based runtime systems and communication libraries for High Performance Computing, especially StarPU and NewMadeleine.

I defended my thesis On the Interactions between HPC Task-based Runtime Systems and Communication Libraries on November 29, 2022.

I developed two main directions in my thesis:

Dynamic broadcasts
To be able to optimize broadcasts appearing in task graphs of StarPU applications, we developed what we called dynamic broadcasts. Functions such as MPI_Bcast cannot be used within StarPU, mainly because recipient processes do not know wheter data comes from a broadcast or a regular point-to-point request, and in the same fashion they do not know other nodes involved in the broadcast. Thus, only the original sender node has all informations to be able to call MPI_Bcast. Accurately detecting broadcasts in the task graph is not straighforward neither.
Our dynamic broadcasts overcome these constraints. The broadcast communication pattern required by the task-based algorithm is detected automatically, then the broadcasting algorithm relies on active messages and source routing, so that participating nodes do not need to know each other and do not need to synchronize. Receiver receives data the same way as it receives point-to-point communication, without having to know it arrives through a broadcast.
Memory contention between computations and communications
To amortize the cost of MPI communications, distributed parallel runtime systems can usually overlap network communications with computations in the hope that it improves global application performance. When using this technique, both computations and communications are running at the same time.
We studied the possible interferences between computations and communications when they are executed in parallel. The main interference that can occur is memory contention between data used by computations and data used by network communications. In some cases, this contention can cause severe slowdown of both computations and communications.
To predict memory bandwidth for computations and for communications when they are executed side by side, we proposed a model taking data locality and contention into account. Elaboration of the model allowed to better understand locations of bottlenecks in the memory system and what are the strategies of the memory system in case of contention.

Publications

A complete list of my publications is available on HAL. The following list, my DBLP page, my Google Scholar page or my ORCiD page contains only my major publications.

Authors are sorted by alphabetical order.

  • First Experiments to Evaluate the Relevance of Task-based Runtime Systems to Implement Large Language Model Applications
    Lionel Eyraud-Dubois, Théo Grandsart, Philippe Swartvagher
    Workshop on Asynchronous Many-Task Systems and Applications (WAMTA) 2026.
  • PALLAS: a generic trace format for large HPC trace analysis
    Catherine Guelque, Valentin Honoré, Philippe Swartvagher, Gaël Thomas, François Trahay
    International Parallel & Distributed Processing Symposium (IPDPS) 2025.
  • Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures
    Sascha Hunold, Philippe Swartvagher, Jesper Larsson Träff, Ioannis Vardas
    Exa-MPI, Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC), 2023.
  • Tracing task-based runtime systems: feedbacks from the StarPU case
    Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher, Samuel Thibault
    Concurrency and Computation: Practice and Experience, 2023.
  • Predicting Performance of Communications and Computations under Memory Contention in Distributed HPC Systems
    Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher
    International Journal of Networking and Computing, 2023, Special Issue on Workshop on Advances in Parallel and Distributed Computational Models 2022.
  • Modeling Memory Contention between Communications and Computations in Distributed HPC Systems
    Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher
    IPDPS 2022 - IEEE International Parallel and Distributed Processing Symposium Workshops (24th Workshop on Advances in Parallel and Distributed Computational Models), May 2022, Lyon / Virtual, France.
  • Interferences between Communications and Computations in Distributed HPC Systems
    Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher
    ICPP 2021 - 50th International Conference on Parallel Processing, Aug 2021, Chicago / Virtual, United States.
  • Using Dynamic Broadcasts to improve Task-Based Runtime Performances
    Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher, Samuel Thibault
    Euro-Par - 26th International European Conference on Parallel and Distributed Computing, Rzadca and Malawski, Aug 2020, Warsaw / Virtual, Poland.