Totoro+ is a DHT-based fully decentralized FL system with locality-aware multi-ring P2P structure, pub/sub forest, and game-theoretic path planning that claims O(log N) hops and 1.2-14x speedup for many concurrent applications on edge nodes.
Totoro: A scalable federated learning engine for the edge,
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cs.DC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Scepsy schedules arbitrary multi-LLM agentic workflows on GPU clusters by constructing Aggregate LLM Pipelines from stable per-LLM execution time shares, then searching fractional GPU allocations, tensor parallelism, and replica counts to achieve up to 2.4x higher throughput and 27x lower latency.
citing papers explorer
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Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System
Totoro+ is a DHT-based fully decentralized FL system with locality-aware multi-ring P2P structure, pub/sub forest, and game-theoretic path planning that claims O(log N) hops and 1.2-14x speedup for many concurrent applications on edge nodes.
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Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines
Scepsy schedules arbitrary multi-LLM agentic workflows on GPU clusters by constructing Aggregate LLM Pipelines from stable per-LLM execution time shares, then searching fractional GPU allocations, tensor parallelism, and replica counts to achieve up to 2.4x higher throughput and 27x lower latency.