Exploiting Multi-Core Parallelism in Blockchain Validation and Construction

2026-02-03

AI Summary

This work investigates how to accelerate block validation and construction using multi-core CPUs while preserving essential blockchain semantics, including transaction ordering, conflict constraints, and block time limits. The problem is formalized as two constrained optimization tasks: minimizing makespan for ordered transaction scheduling and maximizing revenue under bounded runtime through joint transaction selection and scheduling. We propose the first mixed-integer linear programming (MILP) formulation for this setting and, informed by conflict graph analysis from the Ethereum mainnet, design an efficient heuristic algorithm that balances determinism and scalability. Our approach is compared against Solana-style declarative access patterns and greedy revenue-maximization strategies. Experimental results demonstrate that the proposed method significantly reduces processing time while maintaining semantic correctness, quantifying the trade-offs between optimal solutions and heuristics in terms of both runtime and revenue.

Technology Category

• Search and Optimization: Heuristic Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Blockchain validators can reduce block processing time by exploiting multi-core CPUs, but deterministic execution must preserve a given total order while respecting transaction conflicts and per-block runtime limits. This paper systematically examines how validators can exploit multi-core parallelism during both block construction and execution without violating blockchain semantics. We formalize two validator-side optimization problems: (i) executing an already ordered block on \(p\) cores to minimize makespan while ensuring equivalence to sequential execution; and (ii) selecting and scheduling a subset of mempool transactions under a runtime limit \(B\) to maximize validator reward. For both, we develop exact Mixed-Integer Linear Programming (MILP) formulations that capture conflict, order, and capacity constraints, and propose fast deterministic heuristics that scale to realistic workloads. Using Ethereum mainnet traces and including a Solana-inspired declared-access baseline (Sol) for ordered-block scheduling and a simple reward-greedy baseline (RG) for block construction, we empirically quantify the trade-offs between optimality and runtime.

Problem

• blockchain validation
• multi-core parallelism
• deterministic execution
• transaction scheduling
• block construction

Innovation

• multi-core parallelism
• blockchain validation
• Mixed-Integer Linear Programming (MILP)
• deterministic scheduling
• block construction