An Optimizing Operating System: Accelerating Execution With Speculation

To optimize performance, Automatically Scalable Computation (ASC), a Harvard/BU collaboration attempts to auto-parallelize single threaded workloads, reducing any new effort required from programmers to achieve wall clock speedup. SEUSS takes a different approach by splicing a custom operating system into the backend of a high throughput distributed serverless platform, Apache OpenWhisk. SEUSS uses an alternative isolation mechanism to containers, called Library Operating Systems (LibOSs). LibOSs enable a lightweight snapshotting technique. Snapshotting LibOSs enables two counterintuitive results: 1) although LibOSs inherently replicate system state, SEUSS can cache multiplicatively more functions on a node; 2) although LibOSs can suffer bad “first run” performance, SEUSS is able to reduce cold start times by orders of magnitude. By increasing sharing and decreasing deterministic bringup, SEUSS radically reduces the amount of hardware and cycles required to run a FaaS platform.

This project is developed on the Mass Open Cloud.

For more information on this project and the unique partnership that produced it, please see the website of the Red Hat Collaboratory at Boston University.