# FMI: Fast and Cheap Message Passing for Serverless Functions

arXiv: https://arxiv.org/abs/2305.08763 · HTML: https://mlsanity.com/paper/2305.08763/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2023.

## Built on by (most cited first, 3 of 3)

- [Scalable Cosmic AI Inference using Cloud Serverless Computing](https://mlsanity.com/paper/2501.06249/) (2025)
- [High-Performance Serverless Computing: A Systematic Literature Review on Serverless for HPC, AI, and Big Data](https://mlsanity.com/paper/2601.09334/) (2026)
- [Reinforcement Learning-Based Dynamic Management of Structured Parallel Farm Skeletons on Serverless Platforms](https://mlsanity.com/paper/2602.06555/) (2026)

## Abstract (arXiv)

Serverless functions provide elastic scaling and a fine-grained billing model, making Function-as-a-Service (FaaS) an attractive programming model. However, for distributed jobs that benefit from large-scale and dynamic parallelism, the lack of fast and cheap communication is a major limitation. We overcome this limitation and present the FaaS Message Interface (FMI). FMI is an easy-to-use, high-performance framework for general-purpose point-to-point and collective communication in FaaS applications. We support different communication channels and offer a model-driven channel selection according to performance and cost expectations. We model the interface after MPI and show that message passing can be integrated into serverless applications with minor changes, providing portable communication closer to that offered by high-performance systems. In our experiments, FMI can speed up communication for a distributed machine learning FaaS application by up to 162x, while simultaneously reducing cost by up to 397 times.