AI & ML
Weaver: Unlocking Blockchain Transaction Parallelism through State-Decoupled Symbolic Execution
arXiv cs.DC0 views
arXiv:2611.06462v1 Announce Type: new Abstract: Transaction execution remains a major performance bottleneck in blockchains. Existing parallel execution engines are still blocked by slow state accesses on each transaction's critical path, creating a hidden loss of parallelism. This paper presents Weaver, a state-decoupled transaction processing paradigm that enables execution flow to proceed in the absence of concrete state values. Weaver represents states as lightweight symbolic references and records subsequent computation as symbolic expressions while concrete values are fetched on the fly. To handle state-dependent control flow, Weaver predicts the most likely branch direction through hierarchical symbolic pattern matching. Weaver further introduces expression-granular scheduling that evaluates each symbolic expression as soon as its state dependencies are resolved, rather than waiting for the transaction's entire read set, fully exploiting fine-grained intra-transaction parallelism. Evaluation on real Ethereum blocks and synthetic workloads spanning four representative dApps shows that Weaver delivers 41%-63% higher throughput than state-of-the-art parallel execution engines and up to 7.5 times the throughput of serial execution.
Source:https://arxiv.org/abs/2611.06462PreviousPerformance Portability of Out-of-Kernel Optimizations on GPUs: A Molecular Docking Case StudyNextOptimal Subcubic Byzantine Agreement with Plain PKI
Related posts
Scalable Source Selection for Machine Learning Tasks
0arXiv cs.DB
AvalancheBench: Evaluating Enterprise Agent-Driven Semantic Query Processing Through Latent World Recovery
0arXiv cs.DB
ConStruM: A Structure-Guided LLM Framework for Context-Aware Schema Matching
0arXiv cs.DB
From Certified Pairs to a Certified Hub: Reasoner-Checked Crosswalks for the Information Exchange Standard
0arXiv cs.DB
A Comparative Study of Importance Attribution to Columns in Deep Learning over Relational Databases
0arXiv cs.DB
Community Search under Member-Specific Tolerances
0arXiv cs.DB