Hariri Institute Distinguished Lecture - Jonathan Appavoo
- 3:00 pm on Wednesday, April 10, 2013
- 5:00 pm on Wednesday, April 10, 2013
EbbRT - A Modern Approach to Systems Software for Cloud Applications Cloud computing has and continues to transform the kind of computational platforms that an individual can access. Slowly but surely it will be possible to economically access shared public supercomputer systems. Today's cloud computing applications, however, are built on top of legacy operating systems (OS's) that are designed for small-scale shared memory multiprocessors. While these OS's make it possible to construct applications from a rich body of existing middleware and libraries they are in some sense out of sync with the integrated nature of supercomputer systems. These OS are also not the most appropriate building block for Cloud applications. Given the pay-as-you-go model Cloud applications ideally would be able to quickly and dynamically grow and shrink their footprint across the resources a platform. Legacy OS's such as Linux and Windows are not designed for this degree of elasticity or scale. Nor do such operating systems fundamentally incorporate primitives for developing and executing applications that span multiple nodes and exploit the available high-performance communications facilities. On the other hand while the runtime/OS model of supercomputers, such as the IBM Blue Gene family, adopt a dedicated light-weight, kernel model they do not address the needs of elasticity nor do they provide a framework for general purpose service oriented applications. In this talk we describe our work on a new system software architecture and runtime that targets the challenges associated with developing software that can efficiently leveraging such systems for a broad spectrum of applications and use cases. We describe this system software effort in the context of the lessons from our past systems research and our on going effort to develop an "Interactive High-Performance Computing" service for high-speed elastic 3D fetal neuro-imaging reconstruction.