Exploiting Multi-Core Parallelism in Blockchain Validation and Construction

TL;DR

This paper explores how blockchain validators can leverage multi-core CPUs to improve block processing efficiency while maintaining blockchain semantics, through formal optimization models and heuristics tested on real-world data.

Contribution

It introduces formal MILP models and scalable heuristics for multi-core parallelism in blockchain validation and construction, balancing efficiency and correctness.

Findings

Heuristics scale well to realistic workloads.

Trade-offs between optimality and runtime are quantified.

Empirical evaluation on Ethereum and Solana data demonstrates effectiveness.

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.