Exploiting Multi-Core Parallelism in Blockchain Validation and Construction

TL;DR

This work tackles the problem of exploiting multi-core parallelism for blockchain validation and block construction while preserving deterministic, order-equivalent semantics. It introduces two validator-side problems—Ordered-Block Scheduling (OBS) and Parallel-Block Construction (PBC)—and develops exact MILP formulations alongside fast deterministic heuristics, including a 2-1/p approximation for OBS. Through experiments on Ethereum mainnet traces, the authors show that multi-core execution can significantly reduce makespan (OBS) and increase block reward (PBC), with heuristics delivering near-MILP performance in milliseconds and near-linear speedups as cores scale. The study demonstrates practical potential for parallelism in blockchain runtimes and proposes conflict-aware, declarative approaches to block assembly that could inform production systems, while acknowledging limitations like proxy timing and online graph maintenance.

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.

Figures (5)

• Figure 1: Ordered-Block Scheduling - Homogeneous Transactions
• Figure 2: Ordered-Block Scheduling - Homogeneous Transactions. Let $\mathcal{P}_{\text{non}}:=\{ (i,j) : i<j \land (i,j) \notin E \land (j,i) \notin E \}$ be the set of pairs of transactions without conflicts.
• Figure 3: Parallel Block Construction - Homogeneous Transactions
• Figure 4: Parallel Block Construction - Heterogeneous Transactions. Let $\mathcal{P}_{\text{non}}:=\{ (i,j) : i<j \land (i,j) \notin E \land (j,i) \notin E \}$ be the set of pairs of transactions without conflicts.
• Figure : $\textsc{ScoringPBC}({})\xspace$

Theorems & Definitions (1)

• Definition 1: Schedule