Nitro: Boosting Distributed Reinforcement Learning with Serverless Computing

Summary: Nitro leverages serverless functions to spawn ephemeral actors for instant high-concurrency sampling, avoiding serverful startup and scalability bottlenecks. Using a metric-driven, cost-aware actor-scaling heuristic, Nitro yields up to 6× higher final rewards and 42% lower training cost. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14226
Venue: VLDB
Year: 2025
Pagerank: 4.1945683e-05
Overall Rank: 10,866 | 24.41%
DOI: 10.14778/3696435.3696441

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Rank	Cited Paper	Year	Venue	Pagerank
2,791	Towards Demystifying Serverless Machine Learning Training	2021	SIGMOD	8.1206618e-05

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