The International Faculty Development Program (FDP) on High Performance Computing & Data Science is designed to provide an in-depth understanding of the HPC cluster. It will cover topics such as (1) submitting and monitoring jobs (2) optimizing memory and file system usage etc. The lectures organized as a part of the FDP will provide a strong foundation on GPU computing, CUDA APIs, Data analytic tools including Apache Spark. Apache Spark is a powerful open-source distributed computing platform that can be employed as a processing engine for Hadoop, Flume etc.
The FDP will give an overview about Graphics Processing Units (GPUs) that provide enhanced computing power and improved data processing capability when compared to conventional computing architectures. Continuous improvements in GPU computing technology have enabled researchers to achieve substantial performance gains in the areas of climate modeling, materials simulations, financial modeling, MRI imaging, and health science applications. This FDP is designed for researchers who have to manage either very large datasets or very large numbers of small data files for their computations. By conducting practical sessions, the FDP will cover topics like HPC file systems for data upload and staging, storage options, combining text files and general ways to improve performance.
One main objective of the FDP is to give the participants an insight into advanced openMP, MPI and cuda programming concepts like MATLAB in HPC, Ansys tools.
