Clean: A race detector with cleaner semantics

Data races make parallel programs hard to understand. Precise race detection that stops an execution on first occurrence of a race addresses this problem, but it comes with significant overhead. In this work, we exploit the insight that precisely detecting only write-after-write (WAW) and read-after-write (RAW) races suffices to provide cleaner semantics for racy programs. We demonstrate that stopping an execution only when these races occur ensures that synchronization-free-regions appear to be executed in isolation and that their writes appear atomic. Additionally, the undetected racy executions can be given certain deterministic guarantees with efficient mechanisms. We present CLEAN, a system that precisely detects WAW and RAW races and deterministically orders synchronization. We demonstrate that the combination of these two relatively inexpensive mechanisms provides cleaner semantics for racy programs. We evaluate both software-only and hardware-supported CLEAN. The software-only CLEAN runs all Pthread benchmarks from the SPLASH-2 and PARSEC suites with an average 7.8x slowdown. The overhead of precise WAW and RAW detection (5.8x) constitutes the majority of this slowdown. Simple hardware extensions reduce the slowdown of CLEAN's race detection to on average 10.4% and never more than 46.7%.