In 2016, the U.S. Department of Energy established the Exascale Computing Project (ECP) – a joint project of the DOE Office of Science and the DOE National Nuclear Security Administration – that will result in a broadly usable exascale ecosystem and prepare mission critical applications to take advantage of that ecosystem. 

This project aims to create an exascale ecosystem that will:

  • enable classical simulation and modeling applications to tackle problems that are currently out of reach,
  • enable new types of applications to utilize exascale systems, including ones that use machine learning, deep learning, and large-scale data analytics,
  • support widely-used programming models as well as new ones that promise to be more effective on exascale architectures or for applications with new computational patterns, and
  • be suitable for applications that have lower performance requirements currently, thus providing an on ramp to exascale should their future problems require it.

Balancing evolution with innovation is challenging, especially since the ecosystem must be ready to support critical mission needs of DOE, other Federal agencies, and industry, when the first DOE exascale systems are delivered in 2021. The project utilizes a co-design approach that uses over two dozen applications to guide the development of supporting software and R&D on hardware technologies as well as feedback from the latter to influence application development.

This presentation will focus on my assessment of the challenges for achieving an exascale ecosystem, based on the first two years of this project.