Benoît Gallet, Ph.D.
Postdoctoral Scholar
School of Informatics, Computing and Cyber Systems
Northern Arizona University
About
Postdoctoral scholar in Cybersecurity and Computer Science/Ecoinformatics at Northern Arizona University.
Cybersecurity: Porting Number Theoretic Transform (NTT) operations to GPU Tensor Cores for the Post-Quantum Cryptography (PQC) Kyber algorithm.
Ecoinformatics: Modelling tree water and bark beetle stresses using satellite imagery for the state of Arizona, in charge of the large-scale computing aspect.
Expertise in High Performance Computing (HPC), parallel and GPU computing, and algorithm optimizations.
Interested in data science and machine learning, familiar with TensorFlow and Keras.
Looking for job, willing to relocate.
F1 STEM OPT since June 2023, can be extended to Summer 2026.
Skills
Proficient with C, C++, Python, CUDA, OpenMP, OpenMPI
Familiar with Tensorflow and Keras
High-performance computing, parallel and GPU computing, algorithms, data structures, data analysis and clustering algorithms, algorithm optimizations.
Conducting research, presenting, public speaking.
French (native), English (bilingual), German (basic)
Experience
June 2023 - Present
Northern Arizona University, Flagstaff, USA
- Porting and optimizing Number Theoretic Transform (NTT) operations of the Post-Quantum Cryptography (PQC) algorithm Kyber from the CPU to GPU Tensor Cores using CUDA.
- Part of a multi-disciplinary team, focusing on the scalability and performance of the project.
- Designing and developing an algorithm to periodically retrieve satellite images for the state of Arizona and from multiple sources (PlanetLabs, USGS, NASA, and ESA), using Python.
- Designing and developing an algorithm to periodically process new imagery, modeling and computing the trees water and bark beetle stresses of up to 40B pixels. Uses C++, and MPI for distributed computing and scalability.
August 2018 - May 2023
Northern Arizona University, Flagstaff, USA
Worked on data analysis and clustering algorithms, with an emphasis on similarity searches and Euclidean distance calculations:
- Developed GPU workload balancing optimizations (up to 9.7x speedup over prior GPU solution).
- Developed a heterogeneous CPU-GPU algorithm (up to 5.5x speedup over prior GPU solution).
- Developed a GPU algorithm using double precision Tensor Cores (up to 2.2x speedup over prior GPU solution).
May 2022 - August 2022
Northern Arizona University, Flagstaff, USA
- Instructor of record for the CS450 Introduction to Parallel Programming class.
- Taught shared memory parallelism, including pthreads, OpenMP, and vectorization.
- Average course evaluation: 3.86 / 4.
April 2018 - September 2018
Université d’Orléans, Orléans, France and Northern Arizona University, Flagstaff, USA
- Proposed several optimizations for a GPU distance similarity searches algorithm using CUDA.
April 2016 - June 2016
Université d’Orléans and National Center for Scientific Research, Orléans, France
- Ported C code detecting pulse radio signals from neutron stars with a radio telescope and using FFTs to the GPU using CUDA.
Education
Northern Arizona University, Flagstaff, USA
August 2018 - May 2023
Efficient Euclidean Distance Calculations and Distance Similarity Searches: An Examination of Heterogeneous CPU, GPU and Tensor Core Architectures
- Supervised by Dr. Michael Gowanlock
- Worked as Graduate Research Assistant
Université d'Orléans, Orléans, France
September 2016 - September 2018
- Minor in Nomadism, Intelligence and Security
- With Honors
September 2013 - June 2016
Université d'Orléans, Orléans, France
Publications
Posters (2)
Awards and Other