Anthemius: Efficient & Modular Block Assembly for Concurrent Execution

TL;DR

Anthemius is a novel block construction algorithm designed to optimize parallel transaction execution in blockchains, significantly increasing throughput by addressing workload bottlenecks and resource conflicts.

Contribution

It introduces a new block construction method that enhances parallel execution efficiency, outperforming existing approaches across diverse workloads.

Findings

Anthemius enables over twice the transaction throughput compared to baseline methods.

Performance gains are consistent across various workload types.

The algorithm effectively mitigates resource contention bottlenecks.

Abstract

Many blockchains such as Ethereum execute all incoming transactions sequentially significantly limiting the potential throughput. A common approach to scale execution is parallel execution engines that fully utilize modern multi-core architectures. Parallel execution is then either done optimistically, by executing transactions in parallel and detecting conflicts on the fly, or guided, by requiring exhaustive client transaction hints and scheduling transactions accordingly. However, recent studies have shown that the performance of parallel execution engines depends on the nature of the underlying workload. In fact, in some cases, only a 60% speed-up compared to sequential execution could be obtained. This is the case, as transactions that access the same resources must be executed sequentially. For example, if 10% of the transactions in a block access the same resource, the execution cannot meaningfully scale beyond 10 cores. Therefore, a single popular application can bottleneck the execution and limit the potential throughput. In this paper, we introduce Anthemius, a block construction algorithm that optimizes parallel transaction execution throughput. We evaluate Anthemius exhaustively under a range of workloads, and show that Anthemius enables the underlying parallel execution engine to process over twice as many transactions.