FaaSPipe: Fast Serverless Workflows on Distributed Shared Memory

Abstract

Serverless workflows consist of multiple chained functions that pass intermediate data through function invocations. Existing platforms implement data passing via remote storage services that incur significant performance and maintenance overhead. Some recent works optimize data passing with local shared memory but require specialized function scheduling support and are available only in constrained settings. In this paper, we observed that a simplified, peer-to-peer form of distributed shared memory (DSM) is sufficient and efficient to pass data in serverless workflows. With the observation, we propose FaaSPipe, a serverless workflow runtime built on the simplified DSM. FaaSPipe provides PipeFunc, a user-friendly shared memory-based serverless workflow programming model. To support PipeFunc and take full advantage of the simplified DSM, FaaSPipe designs the intra-workflow memory sharing scheme for address space coordination and builds full-duplex memory transfer channels to enable fast, non-blocking peer-to-peer data passing. Evaluation results on real-world workflow applications show that FaaSPipe reduces workflow latency by up to 61% and consumes up to 2.07$\times$ less network traffic compared to state-of-art serverless platforms.