Extended sequential reasoning for data-race-free programs

Effinger-Dean, Laura; Boehm, Hans-J.; Chakrabarti, Dhruva R.; Joisha, Pramod G.

doi:10.1145/1988915.1988922

Cited by 19 publications

(15 citation statements)

References 12 publications

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“…In contrast, an always-on race detector like RADISH guarantees atomicity and isolation of large 2 Annotations can be used to disable race detection for intentional data races, e.g., in lock-free data structures. "interference-free regions" of code across synchronization points [13], a stronger property than sequential consistency.…”

Section: Simpler Memory Modelsmentioning

confidence: 99%

RADISH: Always-on sound and complete race detection in software and hardware

Devietti¹,

Wood²,

Strauss³

et al. 2012

2012 39th Annual International Symposium on Computer Architecture (ISCA)

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Data-race freedom is a valuable safety property for multithreaded programs that helps with catching bugs, simplifying memory consistency model semantics, and verifying and enforcing both atomicity and determinism. Unfortunately, existing software-only dynamic race detectors are precise but slow; proposals with hardware support offer higher performance but are imprecise. Both precision and performance are necessary to achieve the many advantages always-on dynamic race detection could provide.To resolve this trade-off, we propose RADISH, a hybrid hardware-software dynamic race detector that is always-on and fully precise. In RADISH, hardware caches a principled subset of the metadata necessary for race detection; this subset allows the vast majority of race checks to occur completely in hardware. A flexible software layer handles persistence of race detection metadata on cache evictions and occasional queries to this expanded set of metadata. We show that RADISH is correct by proving equivalence to a conventional happens-before race detector.Our design has modest hardware complexity: caches are completely unmodified and we piggy-back on existing coherence messages but do not otherwise modify the protocol. Furthermore,RADISH can leverage type-safe languages to reduce overheads substantially. Our evaluation of a simulated 8-core RADISH processor using PARSEC benchmarks shows runtime overheads from negligible to 2x, outperforming the leading software-only race detector by 2x-37x.

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Section: Simpler Memory Modelsmentioning

confidence: 99%

RADISH: Always-on sound and complete race detection in software and hardware

Devietti¹,

Wood²,

Strauss³

et al. 2012

2012 39th Annual International Symposium on Computer Architecture (ISCA)

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“…The analysis unblocks classical compiler optimizations for accesses free of interferences. Similarly, Effinger-Dean et al [10,11] perform a data-centric classification of regions, called interference free regions (IFR). IFRs are associated to variables (data), extend forward until the first release and backwards until the first acquire operation, and ensure that no other thread accesses the certain data during the IFR execution.…”

Section: Related Workmentioning

confidence: 99%

Automatic detection of extended data-race-free regions

Jimborean

Waern

Ekemark

et al. 2017

2017 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)

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Data-race-free (DRF) parallel programming becomes a standard as newly adopted memory models of mainstream programming languages such as C++ or Java impose data-racefreedom as a requirement.We propose compiler techniques that automatically delineate extended data-race-free regions (xDRF), namely regions of code which provide the same guarantees as the synchronization-free regions (in the context of DRF codes). xDRF regions stretch across synchronization boundaries, function calls and loop back-edges and preserve the data-racefree semantics, thus increasing the optimization opportunities exposed to the compiler and to the underlying architecture. Our compiler techniques precisely analyze the threads' memory accessing behavior and data sharing in shared-memory, general-purpose parallel applications and can therefore infer the limits of xDRF code regions.We evaluate the potential of our technique by employing the xDRF region classification in a state-of-the-art, dualmode cache coherence protocol. Larger xDRF regions reduce the coherence bookkeeping and enable optimizations for performance (6.8%) and energy efficiency (11.7%) compared to a standard directory-based coherence protocol.

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“…Classification of regions has been addressed by Effinger-Dean et al [31], reasoning about interference free regions (IFR) in DRF codes. IFRs are associated to variables (data) and guarantee that while a thread executes the IFR, no other thread can write to the shared variable accessed by the IFR, but not to any shared variable, as in the xDRF classification.…”

Section: Related Workmentioning

confidence: 99%

A Dual-Consistency Cache Coherence Protocol

Ros

Jimborean

2015

2015 IEEE International Parallel and Distributed Processing Symposium

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Abstract-Weak memory consistency models can maximize system performance by enabling hardware and compiler optimizations, but increase programming complexity since they do not match programmers' intuition. The design of an efficient system with an intuitive memory model is an open challenge. This paper proposes SPEL, a dual-consistency cache coherence protocol which simultaneously guarantees the strongest memory consistency model provided by the hardware and yields improvements in both performance and energy consumption. The design of the protocol exploits a compile-time identification of code regions which can be executed under a less restrictive, thus optimized protocol, without harming correctness. Outside these regions, code is executed under a more restrictive protocol which enforces sequential consistency. Compared to a standard directory protocol, we show improvements in performance of 24% and reductions in energy consumption of 32%, on average, for a 64-core chip multiprocessor.

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Extended sequential reasoning for data-race-free programs

Cited by 19 publications

References 12 publications

RADISH: Always-on sound and complete race detection in software and hardware

RADISH: Always-on sound and complete race detection in software and hardware

Automatic detection of extended data-race-free regions

A Dual-Consistency Cache Coherence Protocol

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