Complex problems, such as COVID-19, are being studying computational, prior to be tested experimentally. These complex computational problems require HPC resources, of which must be understood and allocated properly. This requires the user to waste valuable computational time just setting up a job on the HPC system. In order to allow computational scientists to focus on the science, LLNL scientists created Maestro. Maestro is an open-source HPC software tool that automates execution of software by defining required multi-step workflows on HPC resources. The core design of Maestro focuses on encouraging clear workflow communication and documentation, while making consistent execution easier to allow users to focus on science. Maestro’s specifications helps users think about complex workflows in a step-wise, intent-oriented, manner that encourages modularity and tool reuse. These principles are becoming increasingly important as computational science is continuously more present in scientific fields and has started to require a similar rigor to physical experiment. Maestro is currently in use for multiple projects at Lawrence Livermore National Laboratory, has been used to run existing codes including MFEM, and other simulation codes, as well as to train machine-learned models.
Maestro, open-sourced software licensed under the MIT license (LLNL internal case # CP01969)