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.
This blog post introduces the use of deep learning to train a deep neural network to further improve performance; and hybrid architectures.
Hybrid computers that marry CPUs and devices like GPUs and FPGAs are the fastest computers, but they are hard to program. This post explains how deep learning (DL) greatly simplifies programming hybrid computers.
