PhD Students:


Research interests

I am interested in various scheduling and resource partitioning problems in distributed computing.
I am interested in optimizing the execution of applications, and understand the problems application users face when running their code on large-scale platforms.
I mix theoretical studies and experimentation to design models and approximation algorithms in order to propose cost-efficient scheduling strategies for various types of applications.

Recently, I am working on performance analysis for large-scale applications in the PEPR NumPEx.
I am also working on storage problems, in particular on how to efficiently use magnetic tape storage.

Do not hesitate to contact me if you want to collaborate or discuss on these topics!!

--- Post-doc (IN2P3, CNRS) ---

Trustful simulation of high-performance workflows

I extended my PhD work on performance evaluation of in situ processing, where simulation and analytics are co-scheduled on the same computing resources. Determining the best allocation, i.e, how many resources to allocate to each component of an in situ workflow; and mapping, i.e, where and at which frequency to run the data analytics component, is a complex task for which I proposed performance models during my PhD. However, performance assessment of such solutions is crucial to the efficient execution of in situ workflows.
In this project, I developed SimSitu, a faithful simulation framework based on the SimGrid toolkit. SimGrid is capable of accurately simulating distributed applications running on parallel machines. This work was done in collaboration with Oak Ridge National Laboratory (USA) and the University of Southern California (USA). A resulting publication was selected for publication in e-Science'22.

Scheduling user requests on magnetic tapes

The second research direction of my postdoc concerns the scheduling of user requests on magnetic tapes. Magnetic tape is a high-capacity storage technology that is still widely used in computing and data centers to store cold data. When accessing data on tapes, deciding the ordering of the user requests on a tape is crucial to improve the quality of service experienced by users of tape storage systems. In this work, we proposed an exact algorithm for the open problem of minimizing the average service time for read requests on a magnetic tape considered as linear. A resulting paper was accepted for publication in ICAPS'22. In addition, we also publicly released a dataset of tape descriptions and associated user requests extracted from execution logs from the IN2P3 computing center.

--- PhD (Inria, TADaaM team) ---

My PhD focused on resource partitioning, design of scheduling strategies as so as data movement in HPC applications.
I currently work on two complementary research directions.

In the first direction, I am interested in modeling and studying in situ processing, where simulation and analytics are done in parallel to avoid I/O congestion.
This work was done in collaboration with Bruno Raffin, and our results have been published in IJHPCA journal.

The second direction concerns scheduling problems for stochastic applications, for instance Neuroscience applications.
The goal is to propose optimal scheduling strategies for single-core stochastic application running on a reservation-based platform.
Stochastic jobs are jobs whose execution time cannot be determined easily, mostly because they are input-dependent.
They arise from the heterogeneous, dynamic and data-intensive requirements of new emerging fields such as neurosciences
I spent two months in Vanderbilt University, Nashville, USA working on this topic in the group of Padma Raghavan.
Two papers on these topics have been published in IPDPS'19, IPDPS'20, and a journal paper in IEEE Transactions on Parallel and Distributed System.