ABSTRACT
This chapter examines what was the traditional high-performance computing (HPC) – by and large, numerical simulations – is being augmented by computational tools that are very different. To be sure, the face of HPC has hardly been static for more than a few years at a time. The hardware evolutionary transition aside, the bigger impact to what people think of as HPC is the addition of new types of workloads. That is, the expansion of the content of HPC. Specifically, the inclusion of big data or data analytics (DA), and that of artificial intelligence-based methods in the form of machine learning and deep learning. DA methods are now used in HPC applications such as climate modeling and genomics. The same methods are employed by non-HPC applications that now require, due to the size of their datasets, HPC-class systems.
