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Supercharging Scientific Serverless: Slashing Cold Starts with Python UniKernels

DescriptionServerless computing platforms use containers to create custom and isolated execution environments. Thus, the time to serve a function in the Function-as-a-Service (FaaS) paradigm, is dependent on the time to load the necessary container. FaaS platforms try to avoid "cold-starts'', instead pre-loading containers to serve workload. We focus on the problem of rapidly loading Python environments in the Globus Compute (previously funcX) platform. Globus Compute is unique in that it is deployed on HPC systems and thus suffers from costs of shared file systems. We evaluate containers and microvmms (Docker and Firecracker) and propose a new approach using lightweight Python Unikernels. We show considerable speed up in cold-start times using Unikernels.

Author

Jamison Kerney

Illinois Institute of Technology

Event Type

ACM Student Research Competition: Graduate Poster

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