Optimistic Concurrency Control for Real-world Go Programs (Extended Version with Appendix)
Zhizhou Zhang, Milind Chabbi, Adam Welc, Timothy Sherwood

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…
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Taxonomy
TopicsDistributed systems and fault tolerance · Parallel Computing and Optimization Techniques · Advanced Data Storage Technologies
