Plenary: Accelerating Science Discovery - High Performance Simulation , Math and AI

Simon See, NVIDIA Corp. Singapore. ABSTRACT: "Modern scientific discovery relies on advances in data science, mathematics, and artificial intelligence (AI). The combination of these disciplines has led to significant breakthroughs in various fields, including materials science, drug discovery, and chip design. This talk discusses the role of AI-enriched simulation in accelerating science discovery and the use of high-performance computing, math, and AI to drive innovation. Key aspects of AI-enriched simulation include: - Accelerating the discovery process: AI-enriched simulation uses AI to identify the most promising simulations to run on a massive dataset, reducing the computational expense and saving precious time and resources. - Automating complex simulations: AI-enriched simulation makes complex, predictive simulations automatable and user-friendly for researchers without deep computational expertise, removing a critical research bottleneck - Reducing the number of simulations needed: By using AI to analyze data and determine the most promising simulations, AI-enriched simulation can speed up screening by factors of 10-100 times. - Leveraging AI and machine learning: AI-assisted simulations use neural networks and machine learning algorithms to predict complex properties of materials and other systems, bypassing expensive physics-based routines and accelerating the discovery process. - Collaborative research: AI expertise, such as that found at Berkeley Lab, can be combined with traditional research methods to apply AI to various scientific problems, leading to innovative solutions and new discoveries. In summary, the future of scientific discovery lies in the integration of high-performance simulation, math, and AI. By harnessing the power of these technologies, researchers can accelerate the discovery process, automate complex simulations, and unlock new possibilities in various fields.