Implicit parallelism with ordered transactions

Praun, Christoph von; Ceze, Luís; Caşcaval, Călin

doi:10.1145/1229428.1229443

Cited by 82 publications

(53 citation statements)

References 42 publications

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“…The runtime system is then responsible for exploiting available concurrency and verifying data access invariants in order to preserve the semantics of the serial program. Recently, speculative parallel execution was shown to be achievable through thread level speculation [17], [14], [22], [28]. These techniques speculatively execute concurrent threads and revoke execution in the presence of conflicts.…”

Section: Related Workmentioning

confidence: 99%

Alchemist: A Transparent Dependence Distance Profiling Infrastructure

Zhang

Navabi

Jagannathan

2009

2009 International Symposium on Code Generation and Optimization

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Abstract-Effectively migrating sequential applications to take advantage of parallelism available on multicore platforms is a well-recognized challenge. This paper addresses important aspects of this issue by proposing a novel profiling technique to automatically detect available concurrency in C programs. The profiler, called Alchemist, operates completely transparently to applications, and identifies constructs at various levels of granularity (e.g., loops, procedures, and conditional statements) as candidates for asynchronous execution. Various dependences including read-after-write (RAW), write-after-read (WAR), and write-after-write (WAW), are detected between a construct and its continuation, the execution following the completion of the construct. The time-ordered distance between program points forming a dependence gives a measure of the effectiveness of parallelizing that construct, as well as identifying the transformations necessary to facilitate such parallelization. Using the notion of post-dominance, our profiling algorithm builds an execution index tree at run-time. This tree is used to differentiate among multiple instances of the same static construct, and leads to improved accuracy in the computed profile, useful to better identify constructs that are amenable to parallelization. Performance results indicate that the profiles generated by Alchemist pinpoint strong candidates for parallelization, and can help significantly ease the burden of application migration to multicore environments.

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Section: Related Workmentioning

confidence: 99%

Alchemist: A Transparent Dependence Distance Profiling Infrastructure

Zhang

Navabi

Jagannathan

2009

2009 International Symposium on Code Generation and Optimization

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“…Software speculative parallelization was pioneered by Rauchwerger and Padua [21]. While most techniques automatically parallelized doall loops (with limited potential on full applications [15]), several techniques provided a safe interface for expressing possible parallelism [25,26] and likely dependence [27]. BOP used Unix processes to implement parallelism and dependence hints for sequential C/C++ programs [8,12].…”

Section: Related Workmentioning

confidence: 99%

“…To make it programmable, a number of systems provide primitives to mark a speculative task as a safe future [26], an ordered transaction [25], or a possibly parallel region (PPR) [8]. In this paper, we call a speculative task a PPR task and use the support system called BOP for speculation on commodity multicore machines [8,14].…”

Section: Introductionmentioning

confidence: 99%

Access Annotation for Safe Program Parallelization

Ding

Liu

2013

Lecture Notes in Computer Science

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Abstract. The safety of speculative parallelization depends on monitoring all program access to shared data. The problem is especially difficult in softwarebased solutions. Till now, automatic techniques use either program instrumentation, which can be costly, or virtual memory protection, which incurs false sharing. In addition, not all access requires monitoring. It is worth considering a manual approach in which programmers insert access annotations to reduce the cost and increase the precision of program monitoring.This paper presents an interface for access annotation and two techniques to check the correctness of user annotation, i.e. whether all parallel executions are properly monitored and guaranteed to produce the sequential result. It gives a quadratic-time algorithm to check the exponential number of parallel interleavings. The paper then uses the annotation interface to parallelize several programs with uncertain parallelism. It demonstrates the efficiency of program monitoring by a performance comparison with OpenMP, which does not monitor data access or guarantee safety.

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“…The PPR code can be run in parallel with the code after the PPR. It is similar to a safe future [9] or an ordered transaction [8].…”

Section: Introductionmentioning

confidence: 99%