No Provisioned Concurrency: Fast RDMA-codesigned Remote Fork for Serverless Computing
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Abstract (arXiv)
Serverless platforms essentially face a tradeoff between container startup time and provisioned concurrency (i.e., cached instances), which is further exaggerated by the frequent need for remote container initialization. This paper presents MITOSIS, an operating system primitive that provides fast remote fork, which exploits a deep codesign of the OS kernel with RDMA. By leveraging the fast remote read capability of RDMA and partial state transfer across serverless containers, MITOSIS bridges the performance gap between local and remote container initialization. MITOSIS is the first to fork over 10,000 new containers from one instance across multiple machines within a second, while allowing the new containers to efficiently transfer the pre-materialized states of the forked one. We have implemented MITOSIS on Linux and integrated it with FN, a popular serverless platform. Under load spikes in real-world serverless workloads, MITOSIS reduces the function tail latency by 89% with orders of magnitude lower memory usage. For serverless workflow that requires state transfer, MITOSIS improves its execution time by 86%.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Mar 2022.
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Citing papers per year: 2024: 2; 2025: 4; 2026: 2.
8 papers.
- 2024ServerlessLLM: Low-Latency Serverless Inference for Large Language Modelscited by 78
- 2025Beluga: A CXL-Based Memory Architecture for Scalable and Efficient LLM KVCache Managementcited by 11
- 2024KVDirect: Distributed Disaggregated LLM Inferencecited by 8
- 2025PipeBoost: Resilient Pipelined Architecture for Fast Serverless LLM Scalingcited by 2
- 2025WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Servingcited by 2
- 2026SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Servingcited by 1
- 2025BootSeer: Analyzing and Mitigating Initialization Bottlenecks in Large-Scale LLM Trainingcited by 0
- 2026AgileLog: A Forkable Shared Log for Agents on Data Streamscited by 0
- 2026SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving27 Jul 2026
- 2026AgileLog: A Forkable Shared Log for Agents on Data Streams16 Apr 2026
- 2025WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving10 Dec 2025
- 2025Beluga: A CXL-Based Memory Architecture for Scalable and Efficient LLM KVCache Management25 Nov 2025
- 2025BootSeer: Analyzing and Mitigating Initialization Bottlenecks in Large-Scale LLM Training16 Jul 2025
- 2025PipeBoost: Resilient Pipelined Architecture for Fast Serverless LLM Scaling22 Mar 2025
- 2024KVDirect: Distributed Disaggregated LLM Inference13 Dec 2024
- 2024ServerlessLLM: Low-Latency Serverless Inference for Large Language Models25 Jan 2024