# High-Performance Serverless Computing: A Systematic Literature Review on Serverless for HPC, AI, and Big Data

arXiv: https://arxiv.org/abs/2601.09334 · HTML: https://mlsanity.com/paper/2601.09334/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 49 of its 221 references that are in the map.
- First posted on arXiv 14 Jan 2026.

## Builds on (most cited first, 30 of 49)

- [Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider](https://mlsanity.com/paper/2003.03423/) (2020)
- [funcX: A Federated Function Serving Fabric for Science](https://mlsanity.com/paper/2005.04215/) (2020)
- [Serverless Computing: Current Trends and Open Problems](https://mlsanity.com/paper/1706.03178/) (2017)
- [Serverless Computing: One Step Forward, Two Steps Back](https://mlsanity.com/paper/1812.03651/) (2018)
- [Serverless Computing: A Survey of Opportunities, Challenges and Applications](https://mlsanity.com/paper/1911.01296/) (2019)
- [SeBS: A Serverless Benchmark Suite for Function-as-a-Service Computing](https://mlsanity.com/paper/2012.14132/) (2020)
- [OverSketch: Approximate Matrix Multiplication for the Cloud](https://mlsanity.com/paper/1811.02653/) (2018)
- [The server is dead, long live the server: Rise of Serverless Computing, Overview of Current State and Future Trends in Research and Industry](https://mlsanity.com/paper/1906.02888/) (2019)
- [Serving deep learning models in a serverless platform](https://mlsanity.com/paper/1710.08460/) (2017)
- [Next Generation Cloud Computing: New Trends and Research Directions](https://mlsanity.com/paper/1707.07452/) (2017)
- [WfCommons: A Framework for Enabling Scientific Workflow Research and Development](https://mlsanity.com/paper/2105.14352/) (2021)
- [Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence](https://mlsanity.com/paper/2204.09287/) (2022)
- [Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing](https://mlsanity.com/paper/2002.09344/) (2020)
- [Lambada: Interactive Data Analytics on Cold Data using Serverless Cloud Infrastructure](https://mlsanity.com/paper/1912.00937/) (2019)
- [Cold Start Latency in Serverless Computing: A Systematic Review, Taxonomy, and Future Directions](https://mlsanity.com/paper/2310.08437/) (2023)
- [Wukong: A Scalable and Locality-Enhanced Framework for Serverless Parallel Computing](https://mlsanity.com/paper/2010.07268/) (2020)
- [QFaaS: A Serverless Function-as-a-Service Framework for Quantum Computing](https://mlsanity.com/paper/2205.14845/) (2022)
- [Rise of the Planet of Serverless Computing: A Systematic Review](https://mlsanity.com/paper/2206.12275/) (2022)
- [Accelerating Communications in Federated Applications with Transparent Object Proxies](https://mlsanity.com/paper/2305.09593/) (2023)
- [HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges](https://mlsanity.com/paper/1710.08731/) (2017)
- [Improving Robustness of Heterogeneous Serverless Computing Systems Via Probabilistic Task Pruning](https://mlsanity.com/paper/1905.04456/) (2019)
- [Serverless Applications: Why, When, and How?](https://mlsanity.com/paper/2009.08173/) (2020)
- [FMI: Fast and Cheap Message Passing for Serverless Functions](https://mlsanity.com/paper/2305.08763/) (2023)
- [XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing](https://mlsanity.com/paper/2401.04552/) (2024)
- [Software Resource Disaggregation for HPC with Serverless Computing](https://mlsanity.com/paper/2401.10852/) (2024)
- [SeBS-Flow: Benchmarking Serverless Cloud Function Workflows](https://mlsanity.com/paper/2410.03480/) (2024)
- [A lightweight design for serverless Function-as-a-Service](https://mlsanity.com/paper/2010.07115/) (2020)
- [rFaaS: Enabling High Performance Serverless with RDMA and Leases](https://mlsanity.com/paper/2106.13859/) (2021)
- [Using Unused: Non-Invasive Dynamic FaaS Infrastructure with HPC-Whisk](https://mlsanity.com/paper/2211.00717/) (2022)
- [GPU-enabled Function-as-a-Service for Machine Learning Inference](https://mlsanity.com/paper/2303.05601/) (2023)

## Abstract (arXiv)

The widespread deployment of large-scale, compute-intensive applications such as high-performance computing, artificial intelligence, and big data is leading to convergence between cloud and high-performance computing infrastructures. Cloud providers are increasingly integrating high-performance computing capabilities in their infrastructures, such as hardware accelerators and high-speed interconnects, while researchers in the high-performance computing community are starting to explore cloud-native paradigms to improve scalability, elasticity, and resource utilization. In this context, serverless computing emerges as a promising execution model to efficiently handle highly dynamic, parallel, and distributed workloads. This paper presents a comprehensive systematic literature review of 122 research articles published between 2018 and early 2025, exploring the use of the serverless paradigm to develop, deploy, and orchestrate compute-intensive applications across cloud, high-performance computing, and hybrid environments. From these, a taxonomy comprising eight primary research directions and nine targeted use case domains is proposed, alongside an analysis of recent publication trends and collaboration networks among authors, highlighting the growing interest and interconnections within this emerging research field. Overall, this work aims to offer a valuable foundation for both new researchers and experienced practitioners, guiding the development of next-generation serverless solutions for parallel compute-intensive applications.