Optimistic Concurrency Control for Real-world Go Programs (Extended Version with Appendix)

TL;DR

This paper introduces GOCC, a framework that transforms lock-based Go programs into optimistic concurrency versions using HTM, achieving significant performance improvements with minimal regressions.

Contribution

GOCC provides a novel source-to-source transformation approach for Go programs, combining static and dynamic analysis to optimize concurrency with hardware transactional memory.

Findings

Up to 10x performance improvement on Go applications.

Effective detection and transformation of lock regions.

Dynamic learning of HTM usage with perceptron model.

Abstract

We present a source-to-source transformation framework, GOCC, that consumes lock-based pessimistic concurrency programs in the Go language and transforms them into optimistic concurrency programs that use Hardware Transactional Memory (HTM). The choice of the Go language is motivated by the fact that concurrency is a first-class citizen in Go, and it is widely used in Go programs. GOCC performs rich inter-procedural program analysis to detect and filter lock-protected regions and performs AST-level code transformation of the surrounding locks when profitable. Profitability is driven by both static analyses of critical sections and dynamic analysis via execution profiles. A custom HTM library, using perceptron, learns concurrency behavior and dynamically decides whether to use HTM in the rewritten lock/unlock points. Given the rich history of transactional memory research but its lack of adoption in any industrial setting, we believe this workflow, which ultimately produces source-code patches, is more apt for industry-scale adoption. Results on widely adopted Go libraries and applications demonstrate significant (up to 10x) and scalable performance gains resulting from our automated transformation while avoiding major performance regressions.