Dr. Amarpal S Kapoor1
Parallelism and Machine Learning are both critical to achieving performance at all levels of the computing landscape, from small edge devices to the largest supercomputers. Taking advantage of the environments to work with the relevant algorithms requires the right programming tools, techniques, and knowledge. Get to know the paradigms in programming optimization techniques, methodologies that can be adopted for various leading languages and standards like Python, MPI, and openMP to build faster applications.
Learn how to work on moving from HPC to AI workloads and use Intel Python as your ladder to building for Artificial Intelligence, Machine Learning and deep learning.
Dr. Kapoor works as a Software Technical Consulting Engineer at Intel Corporation. His principal focus area at Intel is High Performance Computing (HPC) and Intel Parallel Studio XE cluster tools. Dr. Kapoor provides consultation services to strategic customers and also participates in general customer enabling activities. Before joining Intel, Dr. Kapoor completed his PhD in High Performance Computational Fluid Dynamics (HPC), as a Zienkiewicz scholar, from Swansea University, UK. In the last 10 years, Dr. Kapoor has received 21 awards, distinctions and scholarships.