Over the past decade, the role of atomic scale simulation has expanded from being a retrospective and explanatory technique, to being a powerful discovery and optimization tool. This shift was driven by advances in computer hardware, and the efficiency and accuracy of atomic scale simulation methods. Quantum mechanics (QM) and molecular dynamics (MD) simulation, complemented and extended by data analytics and machine learning (ML), is accelerating materials development and driving innovation by helping to navigate chemical design space; revealing structure-property relationships and identifying promising chemical candidates for experimental realization. The adoption, impact, and applicability has been extended further, due to access to inexpensive “limitless” computational resources on the cloud.
In this presentation we'll describe how deployment of Schrödinger's materials science technologies on Google Cloud's high-performance computing resources can be used to drive materials discovery projects and significantly speed up design cycles. Examples are shown to highlight the impact and future directions of cloud megaruns for large scale computationally driven materials design.