← 研踪 PaperTrailarXiv:2611.17184 · v1
Omakase: Execution Congestion Control through Conflict-Graph Integration in Multi-Proposer Blockchain
Omakase：多提议者区块链中通过冲突图整合实现执行拥塞控制
首次提交 2026-11-13 01:52
版本更新 2026-11-13 01:52
雷达观测 2026-11-13 14:15
摘要
As multi-proposer protocols push consensus throughput, transaction execution has become the dominant bottleneck in blockchains. Layer-1 blockchains parallelize execution either pessimistically (Solana, Sui), requiring upfront state-access declarations and serializing contended transactions, or optimistically (Aptos, Sei, Monad), resolving dependencies at run time but suffering cascading aborts under contention. Both treat blocks in isolation, leaving inter-block parallelism unexploited and most cores idle. We introduce Omakase, a parallel execution framework that combines pre-execution, inter-block conflict-graph integration, and graph-aware Optimistic Concurrency Control (OCC). Replicas use idle cores to pre-execute only the blocks they propose, spreading prediction work across concurrent proposers. After building per-block conflict graphs and identifying their hot resources, a greedy scheduler integrates graphs across the blocks committed in a round, keeping an integration only when a lightweight balance heuristic predicts a parallelism gain. A graph-aware OCC executor then runs the integrated graph, admitting transactions in dependency order, which eliminates aborts when the predicted graph is exact and reduces re-executions when it is not. On 15,000 Ethereum mainnet blocks (~2.4M transactions) and synthetic workloads with configurable contention, Omakase reaches a 2.47x speedup over sequential execution, well above single-block OCC and graph-aware baselines. Against the strongest alternative, which runs the whole round as one optimistic window, Omakase matches mean throughput but is markedly more stable under high contention, because integration bounds how much optimistic work is in flight: this is the congestion control of our title. Integration is not free, but overlapping it with execution across rounds hides 94% of its measured cost in the validator pipeline.
作者备注：15 pages, 7 figures, 8 tables, 6 algorithms
观测到的版本
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v1 · 2026-11-13 01:52 · 最新观测版本
Omakase: Execution Congestion Control through Conflict-Graph Integration in Multi-Proposer Blockchain
As multi-proposer protocols push consensus throughput, transaction execution has become the dominant bottleneck in blockchains. Layer-1 blockchains parallelize execution either pessimistically (Solana, Sui), requiring upfront state-access declarations and serializing contended transactions, or optimistically (Aptos, Sei, Monad), resolving dependencies at run time but suffering cascading aborts under contention. Both treat blocks in isolation, leaving inter-block parallelism unexploited and most cores idle. We introduce Omakase, a parallel execution framework that combines pre-execution, inter-block conflict-graph integration, and graph-aware Optimistic Concurrency Control (OCC). Replicas use idle cores to pre-execute only the blocks they propose, spreading prediction work across concurrent proposers. After building per-block conflict graphs and identifying their hot resources, a greedy scheduler integrates graphs across the blocks committed in a round, keeping an integration only when a lightweight balance heuristic predicts a parallelism gain. A graph-aware OCC executor then runs the integrated graph, admitting transactions in dependency order, which eliminates aborts when the predicted graph is exact and reduces re-executions when it is not. On 15,000 Ethereum mainnet blocks (~2.4M transactions) and synthetic workloads with configurable contention, Omakase reaches a 2.47x speedup over sequential execution, well above single-block OCC and graph-aware baselines. Against the strongest alternative, which runs the whole round as one optimistic window, Omakase matches mean throughput but is markedly more stable under high contention, because integration bounds how much optimistic work is in flight: this is the congestion control of our title. Integration is not free, but overlapping it with execution across rounds hides 94% of its measured cost in the validator pipeline.
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