stats285.github.io
Computers have been used for scientific research since they were invented. Up to recent times, two computational infrastructure paradigms have been largely dominant: workstations/PCs for individual researchers' and small group usage, and batch-queuing systems shared across Departments for larger-scale computation. When new disciplines start making heavy use of quantitative methods and rely on computers for their application, additional flexibility is needed in building and scaling the computational infrastructure -- can IaaS clouds deliver a solution that accomodates this new mix of use cases? Based on my own experience supporting research IT at the University of Zurich, I would like to present a few scientific computing cases that prompted us to evolve our computing infrastructure.
Readings for this lectureThere are no additional required readings for this lecture.
Riccardo Murri currently works at the Services and Support for Science IT unit (S3IT) at the University of Zurich, supporting research groups at UZH and in Swiss academia make best use of computational infrastructures. He holds a PhD in Mathematics from SNS Pisa, and is co-author of ElastiCluster and other software.