HardRace: A Dynamic Data Race Monitor for Production Use

TL;DR

HardRace is a low-overhead, on-the-fly data race detection tool for production environments that combines static analysis and hardware tracing to effectively identify data races with minimal performance impact.

Contribution

HardRace introduces a novel approach combining static analysis and hardware tracing to detect data races efficiently in production, outperforming existing tools in detection and overhead.

Findings

Detects all data races in real-world applications

Maintains less than 2% runtime overhead

Outperforms state-of-the-art tools like ProRace and Kard

Abstract

Data races are critical issues in multithreaded program, leading to unpredictable, catastrophic and difficult-to-diagnose problems. Despite the extensive in-house testing, data races often escape to deployed software and manifest in production runs. Existing approaches suffer from either prohibitively high runtime overhead or incomplete detection capability. In this paper, we introduce HardRace, a data race monitor to detect races on-the-fly while with sufficiently low runtime overhead and high detection capability. HardRace firstly employs sound static analysis to determine a minimal set of essential memory accesses relevant to data races. It then leverages hardware trace instruction, i.e., Intel PTWRITE, to selectively record only these memory accesses and thread synchronization events during execution with negligible runtime overhead. Given the tracing data, HardRace performs standard data race detection algorithms to timely report potential races occurred in production runs. The experimental evaluations show that HardRace outperforms state-of-the-art tools like ProRace and Kard in terms of both runtime overhead and detection capability -- HardRace can detect all kinds of data races in read-world applications while maintaining a negligible overhead, less than 2% on average.