FaaS Is Not Enough: Serverless Handling of Burst-Parallel Jobs

TL;DR

This paper presents a new serverless approach for burst-parallel jobs that overcomes FaaS limitations by enabling group invocation, improving locality, reducing latency, and significantly accelerating applications like TeraSort and PageRank.

Contribution

We introduce a group invocation primitive for serverless computing, enabling efficient burst-parallel job handling with improved locality and communication.

Findings

Reduces job invocation latency by 2×

Achieves 13× speed-up for TeraSort

Cuts remote communication by 98.5% for PageRank

Abstract

Function-as-a-Service (FaaS) struggles with burst-parallel jobs due to needing multiple independent invocations to start a job. The lack of a group invocation primitive complicates application development and overlooks crucial aspects like locality and worker communication. We introduce a new serverless solution designed specifically for burst-parallel jobs. Unlike FaaS, our solution ensures job-level isolation using a group invocation primitive, allowing large groups of workers to be launched simultaneously. This method optimizes resource allocation by consolidating workers into fewer containers, speeding up their initialization and enhancing locality. Enhanced locality drastically reduces remote communication compared to FaaS, and combined with simultaneity, it enables workers to communicate synchronously via message passing and group collectives. This makes applications that are impractical with FaaS feasible. We implemented our solution on OpenWhisk, providing a communication middleware that efficiently uses locality with zero-copy messaging. Evaluations show that it reduces job invocation and communication latency, resulting in a 2$\times$ speed-up for TeraSort and a 98.5% reduction in remote communication for PageRank (13$\times$ speed-up) compared to traditional FaaS.