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.
Additional Project Information
Seuss is enabled by the Mass Open Cloud.
Please also visit the Red Hat Research Seuss page.
- Contact: Jonathan Appavoo
- Ulrich Drepper
- Tommy Unger
- Han Dong
- Yara Awad
- Orran Krieger
- James Cadden
- Amos Waterland