Maxime GONTHIER

Contact and information

I completed my PhD at ENS Lyon in the field of Computer Science. I worked in the ROMA team at the LIP laboratory under the supervision of Loris Marchal (ENS Lyon, CNRS) and in the STORM team at INRIA Bordeaux with the supervision of Samuel Thibault (Université de Bordeaux, Inria).

Email:

maxime (dot) gonthier (at) ens-lyon.fr

Research interests

My research focuses on scheduling problems. I study more specifically the issue of scheduling task sharing data under memory constraint. To solve this problem I create algorithms and implement them in the StarPU runtime.

I also had the chance to collaborate with the Division of Scientific Computing at Uppsala University. During this collaboration I worked on the subject of batch scheduling of jobs needing large input files.

PhD defense

My PhD defense took place the September 25^th, 2023 in the LaBRI in Bordeaux, France. The subject is Scheduling Under Memory Constraint in Task-based Runtime Systems.
Abstract: Hardware accelerators, such as GPUs, now provide a large part of the computational power used for scientific simulations. GPUs come with their own limited memory and are connected to the main memory of the machine via a bus with limited bandwidth. Scientific simulations often operate on very large data, to the point of not fitting in the limited GPU memory. In this case, one has to turn to out-of-core computing, where data movement quickly becomes a performance bottleneck. During this thesis, we worked on the problem of scheduling for a task-based runtime to improve data locality in an out-of-core setting, in order to reduce data movements. We designed strategies for both task scheduling and data eviction from limited memories. We implemented them in the StarPU runtime and compared them to existing scheduling techniques. Our strategies achieves significantly better performance when scheduling tasks on multiple GPUs with limited memory, as well as on multiple CPU cores with limited main memory.

My PhD manuscrit is available here. A capture of my PhD defense is available:

Publications

Authors	Link	Year	Conference/Journal	Type of publication
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT	A generic scheduler to foster data locality for GPU and out-of-core task-based applications	2023	~	Research report
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT	Memory-Aware Scheduling Of Tasks Sharing Data On Multiple GPUs	2023	ISC	Poster
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT, Elisabeth LARSSON, Carl NETTELBLAD	Locality-aware batch scheduling of I/O intensive workloads	2023	~	Research report
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT	Taming data locality for task scheduling under memory constraint in runtime systems	2023	Future Generation Computer Systems	Journal
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT	Memory-Aware Scheduling of Tasks Sharing Data on Multiple GPUs with Dynamic Runtime Systems	2022	IPDPS	Conference
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT	Locality-Aware Scheduling of Independent Tasks for Runtime Systems (Extended Version)	2021	~	Research report
Maxime GONTHIER, Loris MARCHAL, Samuel THIBAULT	Locality-Aware Scheduling of Independent Tasks for Runtime System	2021	EuroPar	Workshop

Programming projects

Most of our research papers are associated with a source code in order to reproduce the presented results.

For instance, you can find our first algorithm developed to statically schedule task under memory constraint here and our second algorithm that dynamically schedule tasks here.

The code I developed during my research collaboration in Uppsala is a batch simulator as well as 4 schedulers and is available here.

I implemented into the StarPU runtime 5 new schedulers and a new eviction policy.

Teaching