Framework: Software: Next-Generation Cyberinfrastructure for Large-Scale Computer-Based Scientific Analysis and Discovery

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

Recent revolutions in data availability have radically altered activities across many fields within science, industry, and government. For instance, contemporary simulations medication properties can require the computational power of entire data centers, and recent efforts in astronomy will soon generate the largest image datasets in history. In such extreme environments, the only viable path forward for scientific discovery hinges on the development and exploitation of next-generation computational cyberinfrastructure of supercomputers and software. The development of this new computational infrastructure demands significant engineering resources, so it is paramount to maximize the infrastructure's potential for high impact and wide adoption across as many technical domains as possible. Unfortunately, despite this necessity, existing development processes often produce software that is limited to specific hardware, or requires additional expertise to use properly, or is overly specialized to a specific problem domain. Such "single-use" software tools are limited in scope, leading to underutilization by the wider scientific community. In contrast, this project seeks to develop methods and software for computer-based scientific analysis that are sufficiently powerful, flexible and accessible to (i) enable domain experts to achieve significant advancements within their domains, and (ii) enable innovative use of advanced computational techniques in unexpected scientific, technological and industrial applications. This project will apply these tools to a wide variety of specific scientific challenges faced by various research teams in astronomy, medicine, and energy management. These teams plan on using the proposed work to map out new star systems, develop new life-saving medications, and design new power systems that will deliver more energy to a greater number of homes and businesses at a lower cost than existing systems. Finally, this project will seek to leave a legacy of sustained societal benefit by educating students and practitioners in the broader scientific and engineering communities via exposure to state-of-the-art computational techniques. Through close collaboration with research teams in statistical astronomy, pharmacometrics, power systems optimization, and high-performance computing, this project will deliver cyberinfrastructure that will effectively and effortlessly enable the next generation of computer-based scientific analysis and discovery. To ensure the practical applicability of the developed cyberinfrastructure, the project will focus on three target scientific applications: (i) economically viable decarbonization of electrical power networks, (ii) real-time analysis of extreme-scale astronomical image data, and (iii) pharmacometric modeling and simulation for drug analysis and discovery. While tackling these specific problems will constitute an initial stress test of the proposed cyberinfrastructure, it is the ultimate goal of the project that the developed tools be sufficiently performant, accessible, composable, flexible and adaptable to be applied to the widest possible range of problem domains. To achieve this vision, the project will build and improve various software tools for computational optimization, machine learning, parallel computing, and model-based simulation. Particular attention will be paid to the proposed cyberinfrastructure's composability with new and existing tools for scientific analysis and discovery. The pursuit of these goals will require the design and implementation of new programming language abstractions to allow close integration of high-level language features with low-level compiler optimizations. Furthermore, maximally exploiting proposed cyberinfrastructure will require research into new methods that combine state-of-the-art techniques from optimization, machine learning, and high-performance computing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.