CAREER: Exploiting Parallel Heterogeneous Architectures to Enable Time-domain Astronomy in the LSST era

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Recent and near future scientific instruments will generate large amounts of data. One example of such an instrument is the Vera C. Rubin Observatory that will carry out the Legacy Survey of Space and Time (LSST) over a ten year period. This astronomical survey has the potential to advance many fields of astronomy, and may even lead to the development of new fields of scientific inquiry. However, the large data volume implies that many processors will need to be used to process the data within a reasonable amount of time. This project creates new technologies and algorithms that can utilize a large number of processors. In particular, the project harnesses the power of both standard central processing units (CPUs) and graphics processing units (GPUs) that are good at processing many data items simultaneously. The developed technologies are designed to use the data from LSST and find interesting events in the Solar System. Once an interesting event is detected on a given astronomical object, alerts are sent to the astronomy community so that they can use additional telescopes to further study these objects. Without the technologies developed in this project, astronomers will miss out on opportunities to study transient phenomena. The project integrates several teaching activities that ensure both computer scientists and astronomers receive the necessary training to exploit future generation computer systems. The project includes mentoring undergraduate and graduate students. In addition, the local community will be engaged through outreach activities that promote science, technology, engineering, and mathematical fields, particularly through activities targeting K-12 students. The project serves the national interest, as stated by NSF's mission, by promoting the progress of science, and to advance the national health, prosperity, and welfare. The Vera C. Rubin Observatory will have unprecedented time domain capabilities. However, LSST will generate large volumes of data that need to be examined in order to realize many scientific goals. This project focuses on LSST supporting cyberinfrastructure (CI) in the context of Solar System science. Fast outlier detection is needed to enable rapid follow up by other facilities to ensure that transient events in the Solar System and objects with intrinsically unusual properties are discovered. To ensure rapid detection capabilities, the outlier detection algorithms will exploit heterogeneous CPU and GPU architectures. Furthermore, heterogeneous computing will be employed where the work is distributed between the CPU and GPU. Also, the project examines using application specific integrated circuits on modern GPU hardware, such as tensor and ray tracing cores as applied to a broader range of applications than matrix multiplication and ray tracing. Algorithmic transformations are needed to exploit these heterogeneous processors; consequently, a unifying framework is developed that models the performance of these algorithms as executed on these architectures. This framework and novel parallel and scalable algorithms provide foundational CI that will enable the LSST to successfully explore the Solar System, understand its origins, and identify potentially hazardous asteroids, among other scientific objectives.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.