Director of High Performance Computing and Machine Learning in the Financial Risk division, SAS
Henry Bequet is Director of High Performance Computing and Machine Learning in the Financial Risk division of SAS. In that capacity, he leads the development of a high-performance solution that can run SAS code on thousands of CPU and GPU cores for advanced models that use techniques like Black-Scholes, Binomial Evaluation, and Monte-Carlo simulations. Henry has more than 35 years of industry experience and 15 years of high-performance analytics practice. He has published two books and several papers on server development and machine learning.
By This Author
Deep Learning for Numerical Applications with SAS®
By Henry G. Bequet
Dive into deep learning! Written by an expert in high-performance analytics, Deep Learning for Numerical Applications with SAS® introduces a new field: Deep Learning for Numerical Applications (DL4NA). It introduces deep learning concepts in SAS along with step-by-step techniques that allow you to easily reproduce the examples on your high-performance analytics systems. It also discusses the latest hardware innovations that can power your SAS programs from many-core CPUs to GPUs to FPGAs to ASICs.
- Jim Blum is a Professor of Statistics at the University of North Carolina Wilmington where he has developed and taught original courses in SAS programming for the university for more than 15 years. These courses cover topics in SAS/BASE, SAS/SQL, SAS/STAT, and macro language.
- Jack Shostak, Associate Director of Statistics, manages a group of statistical programmers at the Duke Clinical Research Institute.
- Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.