High Performance Systems and Data Management (HPC/IA)

I chose the CIDM course because I wanted to acquire in-depth knowledge of both the infrastructure and cloud computing sides.

This course gave me the tools to understand many components of today's IT, from the operating system to the operation of a data center and parallel computing libraries. This knowledge, valued in the fields of HPC and cloud computing, helped me integrate easily into a company.

I now work for Qarnot Computing, an ecological cloud provider that reuses the waste heat from servers to heat swimming pools, buildings or heat networks.

My missions mainly involve maintaining the operation of the distributed computing platform and developing software on the infrastructure side.

After much hesitation between the CIDM and GL courses, I finally chose the first because it seemed to provide rare and transversal skills, ranging from low-level computing to numerical simulation in the context of intensive computing.

The course allowed me, among other things, to better understand how a computer or a computing cluster executed code and how to optimize the performance of all associated processes. This knowledge allowed me to adapt quickly in a company.

Today, I am a software engineer at Qarnot Computing, a startup that reuses the fatal heat of computer servers to heat swimming pools, buildings, warehouses, heat networks, etc. We provide a cloud platform adapted for HPC-type workloads (CFD simulations, 3D rendering, etc.) and I work on several subjects including optimizing the performance of our remote desktop solution.

I decided to pursue the CIDM/HPC track due to my interest in "low-level" programming, computer hardware architecture, and performance. I am currently a PhD student at CEA, and my work focuses on optimizing parallel programs. This track opens up many opportunities, whether in research at CEA, in the industrial sector where there is a growing demand for cluster utilization, or in the startup world.

I joined ENSIIE with the goal of working in low-level computing while also having the opportunity to explore machine learning and deep learning. The creation of the program coincided with my arrival, allowing me to discover work on computing systems, whether as a system administrator (LC, vc, ASE, RIAL), data scientist (IPS, PSA), or developer (PBT, PP). Additionally, the broad spectrum of the training opens up numerous career opportunities in Big Data and DevOps positions. Today, I am a system administrator at Bull Atos at TGCC.