Computing systems with a large number of processing units are increasingly common, both in the form of processors employing multiple execution cores (e.g., multi-core CPUs, GPUs, accelerators), or computing clusters with a large number of nodes. These many- core architectures bring up new capabilities, opportunities, as well as challenges. Adapting applications effectively use these architectures has involved a significant amount of effort, not only in code modifications, but also in developing the programming environment. However, several industry trends seem to indicate that large-scale homogeneous platforms, which contain a single type of compute engine with a relatively straightforward memory hierarchy, will soon be a thing of the past. The expansion of heterogeneity in multiple dimensions - compute, memory, storage, systems, software, applications, and usage models – leverages an extreme heterogeneity scenario that will affect both the processor industry but also the software industry, with strong repercussions on programming models, scientific workflows and data management systems. In this talk we examine how high-performance computing has changed over the last 10 years, what are the current projects towards exaflop computing, and look toward the future in terms of trends.