Occupy the Cloud: Distributed Computing for the 99%
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Abstract (arXiv)
Distributed computing remains inaccessible to a large number of users, in spite of many open source platforms and extensive commercial offerings. While distributed computation frameworks have moved beyond a simple map-reduce model, many users are still left to struggle with complex cluster management and configuration tools, even for running simple embarrassingly parallel jobs. We argue that stateless functions represent a viable platform for these users, eliminating cluster management overhead, fulfilling the promise of elasticity. Furthermore, using our prototype implementation, PyWren, we show that this model is general enough to implement a number of distributed computing models, such as BSP, efficiently. Extrapolating from recent trends in network bandwidth and the advent of disaggregated storage, we suggest that stateless functions are a natural fit for data processing in future computing environments.
Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Feb 2017.
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Citing papers per year: 2021: 6; 2022: 2; 2023: 1; 2024: 4; 2025: 2; 2026: 2.
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- 2021Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threadscited by 51
- 2021LocalNewton: Reducing Communication Bottleneck for Distributed Learningcited by 15
- 2021GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategycited by 8
- 2021Distributed Double Machine Learning with a Serverless Architecturecited by 5
- 2022Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Boundscited by 5
- 2021Serverless Data Science -- Are We There Yet? A Case Study of Model Servingcited by 3
- 2025What Limits Agentic Systems Efficiency?cited by 3
- 2022FedLesScan: Mitigating Stragglers in Serverless Federated Learningcited by 2
- 2023Laminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completioncited by 2
- 2024Computing in the Era of Large Generative Models: From Cloud-Native to AI-Nativecited by 2
- 2024FSD-Inference: Fully Serverless Distributed Inference with Scalable Cloud Communicationcited by 1
- 2024Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasingcited by 1
5 more
- 2021Accelerating Serverless Computing by Harvesting Idle Resourcescited by 0
- 2024StraightLine: An End-to-End Resource-Aware Scheduler for Machine Learning Application Requestscited by 0
- 2025AI Factories: It's time to rethink the Cloud-HPC dividecited by 0
- 2026Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioningcited by 0
- 2026ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platformcited by 0
- 2026ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platform29 Jul 2026
- 2026Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning23 Apr 2026
- 2025What Limits Agentic Systems Efficiency?18 Oct 2025
- 2025AI Factories: It's time to rethink the Cloud-HPC divide16 Sep 2025
- 2024Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing2 Oct 2024
- 2024StraightLine: An End-to-End Resource-Aware Scheduler for Machine Learning Application Requests25 Jul 2024
- 2024FSD-Inference: Fully Serverless Distributed Inference with Scalable Cloud Communication22 Mar 2024
- 2024Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native17 Jan 2024
- 2023Laminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completion1 Sep 2023
- 2022FedLesScan: Mitigating Stragglers in Serverless Federated Learning10 Nov 2022
- 2022Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds18 Mar 2022
- 2021Accelerating Serverless Computing by Harvesting Idle Resources28 Aug 2021
5 more
- 2021Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads24 May 2021
- 2021LocalNewton: Reducing Communication Bottleneck for Distributed Learning16 May 2021
- 2021GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy21 Apr 2021
- 2021Serverless Data Science -- Are We There Yet? A Case Study of Model Serving4 Mar 2021
- 2021Distributed Double Machine Learning with a Serverless Architecture11 Jan 2021
- 2025What Limits Agentic Systems Efficiency?cited by 3
- 2025What Limits Agentic Systems Efficiency?18 Oct 2025
- 2021Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threadscited by 51
- 2021LocalNewton: Reducing Communication Bottleneck for Distributed Learningcited by 15
- 2021GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategycited by 8
- 2021Distributed Double Machine Learning with a Serverless Architecturecited by 5
- 2022Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Boundscited by 5
- 2021Serverless Data Science -- Are We There Yet? A Case Study of Model Servingcited by 3
- 2022FedLesScan: Mitigating Stragglers in Serverless Federated Learningcited by 2
- 2023Laminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completioncited by 2
- 2024Computing in the Era of Large Generative Models: From Cloud-Native to AI-Nativecited by 2
- 2024FSD-Inference: Fully Serverless Distributed Inference with Scalable Cloud Communicationcited by 1
- 2024Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasingcited by 1
- 2021Accelerating Serverless Computing by Harvesting Idle Resourcescited by 0
12 most cited of 16 All 16 (JSON)
- 2026ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platform29 Jul 2026
- 2026Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning23 Apr 2026
- 2025AI Factories: It's time to rethink the Cloud-HPC divide16 Sep 2025
- 2024Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing2 Oct 2024
- 2024StraightLine: An End-to-End Resource-Aware Scheduler for Machine Learning Application Requests25 Jul 2024
- 2024FSD-Inference: Fully Serverless Distributed Inference with Scalable Cloud Communication22 Mar 2024
- 2024Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native17 Jan 2024
- 2023Laminar: A New Serverless Stream-based Framework with Semantic Code Search and Code Completion1 Sep 2023
- 2022FedLesScan: Mitigating Stragglers in Serverless Federated Learning10 Nov 2022
- 2022Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds18 Mar 2022
- 2021Accelerating Serverless Computing by Harvesting Idle Resources28 Aug 2021
- 2021Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads24 May 2021
12 newest of 16 All 16 (JSON)