Welcome to PEARC20! PEARC20’s theme is “Catch the Wave.” This year’s theme embodies the spirit of the community’s drive to stay on pace and in front of all the new waves in technology, analytics, and a globally connected and diverse workforce. We look forward to this year’s PEARC20 virtual meeting, where we can share scientific discovery and craft the future infrastructure.
The conference will be held in Pacific Time (PT) and the times listed below are in Pacific Time.
The connection information for all PEARC20 workshops, tutorials, plenaries, track presentations, BOFs, Posters, Visualization Showcase, and other affiliated events, are in the PEARC20 virtual conference platform, Brella. If you have issues joining Brella, please email pearcinfo@googlegroups.com.
Cloud computing lets researchers match computational infrastructure to the needs of specific research applications, execute without queue wait times, scale to meet workload demands, and share and reproduce scientific analyses. However, there are many ways to run high performance computing (HPC) applications in the cloud, and selecting the best and most cost- effective way can be daunting. This tutorial describes the specific benefits of cloud computing to research workloads, defines cloud-based computational methods such as auto-scaling and serverless computing, and teaches best practices for computationally intensive research workloads in the cloud. Attendees will apply what they have learned in a hands-on tutorial on Amazon Web Services (AWS) . We will use specific scientific examples from genomics and weather forecasting to illustrate the appropriate use of both serverless batch computation and tightly-coupled clusters running applications with the Message Passing Interface (MPI) library. We will describe how to parallelize workflows and ensure reproducibility through workflow management systems and containers, illustrated with the open-source software NextFlow. We will also cover practical aspects of cloud computing for research, such as budgeting and minimizing cost, leveraging ongoing technological advances, sharing data and research infrastructure, and adapting to changing research methods and standards.
