Convergence of Artificial Intelligence and High Performance Computing on NSF-supported Cyberinfrastructure

Significant investments to upgrade or construct large-scale scientific facilities demand commensurate investments in R&D to design algorithms and computing approaches to enable scientific and engineering breakthroughs in the big data era. The remarkable success of Artificial Intelligence (AI) algorithms to turn big-data challenges in industry and technology into transformational digital solutions that drive a multi-billion dollar industry, which play an ever increasing role shaping human social patterns, has promoted AI as the most sought after signal processing tool in big-data research. As AI continues to evolve into a computing tool endowed with statistical and mathematical rigor, and which encodes domain expertise to inform and inspire AI architectures and optimization algorithms, it has become apparent that single-GPU solutions for training, validation, and testing are no longer sufficient. This realization has been driving the confluence of AI and high performance computing (HPC) to reduce time-to-insight and to produce robust, reliable, trustworthy, and computationally efficient AI solutions. In this white paper, we present a summary of recent developments in this field, and discuss avenues to accelerate and streamline the use of HPC platforms to design accelerated AI algorithms.