NSF Award
2311709
Advances in computer simulations have made scientific discoveries more accessible. However, with the evolution of computing technology, each new generation of hardware and software presents unique performance and reliability challenges. These challenges must be addressed to fully harness the potential of these evolving technologies. SPADE is a project aimed to tackle these issues head-on. At its core, SPADE builds on the PAPI performance monitoring library - a tool used by the High-Performance Computing (HPC) community for over two decades. SPADE aims to enhance this legacy by creating methods that can assess and improve performance and accuracy on a wide range of advanced and evolving hardware and software technologies. This endeavor is not just about improving computational science but also about fostering diversity and education of a new generation of application scientists, engineers, and computer scientists. By providing an understanding of, and the ability to, navigate the intricate details of emerging technologies in the computing realm, SPADE is directly contributing to the advancement of this field. This will also democratize access to HPC, allowing a more diverse range of researchers and institutions to contribute to scientific discovery. Moreover, as SPADE aims to improve the capabilities of computer simulations, it enhances the ability to tackle a broad range of challenges - from understanding climate change to drug discovery. In essence, beyond advancing the HPC field, SPADE intends delivering a real-world impact by unlocking the full potential of computational science.<br/><br/>The SPADE project focuses on advancing the monitoring, optimization, evaluation, and decision-making capabilities for extreme-scale systems. These critical capabilities are pivotal for both the High-Performance Computing (HPC) community and the scientific applications community that leverage these systems. With the evolution of HPC resources toward extreme scale, there is an increasing need for integrated performance and accuracy analysis frameworks to understand and mitigate performance and reliability challenges. To meet these needs, SPADE aims to deliver software and application programming interfaces (APIs) that broaden support for heterogeneity and scalability across a diverse range of computing platforms, including emerging vendor technologies. The SPADE project intends to utilize the established PAPI performance monitoring library to address the demands of scientific and machine learning applications effectively. Specifically, SPADE's mission includes: (1) developing monitoring capabilities for innovative and advanced technologies across the hardware stack; (2) designing novel abstractions that encapsulate the internal behavior of software components and facilitate interoperability across the software stack; (3) implementing a new performance and accuracy analysis framework that capitalizes on the efficiency and flexibility of C++'s object-oriented nature; (4) integrating new analysis functionality with various software stack layers and scientific and machine learning applications; and (5) examining new accuracy vs. performance trade-offs introduced with low-precision floating-point types. In essence, SPADE facilitates innovations in cyberinfrastructure development by enabling efficient and comprehensive resource utilization of extreme-scale platforms.<br/><br/>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.
