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Pilotfish: Distributed Execution for Scalable Blockchains

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arxiv 2401.16292 v3 pith:KEDWYR2Z submitted 2024-01-29 cs.DC

classification cs.DC
keywords pilotfishexecutionelasticityscalablesystemsblockchainblockchainschallenges
verification ladder T0 review T1 audit T2 compute T3 formal
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Scalability is a crucial requirement for modern large-scale systems, enabling elasticity and ensuring responsiveness under varying load. While cloud systems have achieved scalable architectures, blockchain systems remain constrained by the need to over-provision validator machines to handle peak load. This leads to resource inefficiency, poor cost scaling, and limits on performance. To address these challenges, we introduce Pilotfish, the first scale-out transaction execution engine for blockchains. Pilotfish enables validators to scale horizontally by distributing transaction execution across multiple worker machines, allowing elasticity without compromising consistency or determinism. It integrates seamlessly with the lazy blockchain architecture, completing the missing piece of execution elasticity. To achieve this, Pilotfish tackles several key challenges: ensuring scalable and strongly consistent distributed transactions, handling partial crash recovery with lightweight replication, and maintaining concurrency with a novel versioned-queue scheduling algorithm. Our evaluation shows that Pilotfish scales linearly up to at least eight workers per validator for compute-bound workloads, while maintaining low latency. By solving scalable execution, Pilotfish brings blockchains closer to achieving end-to-end elasticity, unlocking new possibilities for efficient and adaptable blockchain systems.

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Remora: Scale-out Deterministic Execution for Smart Contracts

    cs.DC 2026-07 conditional novelty 6.5 of 10

    Remora scales deterministic smart-contract execution inside a single validator to ~250k TPS via asymmetric dispatch, object versioning with leases, and pre-consensus stateless work plus subgraph scheduling.

  2. Data-Driven and Participatory Approaches toward Neuro-Inclusive AI

    cs.HC 2025-06 conditional novelty 6.0 of 10

    Across five studies, the dissertation documents exclusion of autistic perspectives in human-robot interaction research and releases AUTALIC, a Reddit-derived benchmark for anti-autistic hate speech detection.

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