A scalable approach to thread-level speculation

Steffan, J. Gregory; Colohan, Christopher B.; Zhai, Antonia; Mowry, Todd C.

doi:10.1145/342001.339650

Cited by 109 publications

(120 citation statements)

References 28 publications

(26 reference statements)

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“…However, it creates complex chains of dependences among speculative tasks. Thus, upon detecting mispeculation, most TLS schemes abort the task that caused the violation and all later speculative tasks [25,28,61,66,68]. TCC [29] and Bulk [11] are the exception: they do not forward data and only abort later readers when the earlier writer commits.…”

Section: Background On Hw Support For Speculative Parallelismmentioning

confidence: 99%

“…To address this, we contribute a novel conflict detection scheme based on eager version management that allows both forwarding speculative data and selective aborts of dependent tasks. Commit serialization: Prior TLS schemes enforce inorder commits by passing a token among ready-to-commit tasks [28,61,66,68]. Each task can only commit when it has the token, and passes the token to its immediate successor when it finishes committing.…”

Section: Background On Hw Support For Speculative Parallelismmentioning

confidence: 99%

“…By contrast, most TLS systems use lazy versioning (buffering speculative data in caches) or more expensive multiversioning [11,25,28,29,56,60,61,66,68,69] to limit the cost of aborts. Some early TLS schemes are eager [25,80], and they still suffer from the limitations discussed in Sec.…”

Section: Speculative Execution and Versioningmentioning

confidence: 99%

“…Several TLS schemes expose timestamps to software for different purposes, such as letting the compiler schedule loop iterations in Stampede [68], speculating across barriers in TCC [29], and supporting out-of-order spawn of speculative function calls in Renau et al [61]. These schemes work well for their intended purposes, but cannot queue or buffer tasks with arbitrary timestampsthey can only spawn new work if there is a free hardware context.…”

Section: Additional Related Workmentioning

confidence: 99%

“…Moreover, many of these algorithms rarely have true data dependences among tasks, and their maximum achievable parallelism exceeds 100×. It may seem that thread-level speculation (TLS) [28,60,66,68], which speculatively parallelizes sequential programs, could exploit this parallelism. However, this is not the case due to two reasons (Sec.…”

Section: Introductionmentioning

confidence: 99%

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A scalable architecture for ordered parallelism

Jeffrey¹,

Subramanian²,

Yan³

et al. 2015

Proceedings of the 48th International Symposium on Microarchitecture

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We present Swarm, a novel architecture that exploits ordered irregular parallelism, which is abundant but hard to mine with current software and hardware techniques. In this architecture, programs consist of short tasks with programmer-specified timestamps. Swarm executes tasks speculatively and out of order, and efficiently speculates thousands of tasks ahead of the earliest active task to uncover ordered parallelism. Swarm builds on prior TLS and HTM schemes, and contributes several new techniques that allow it to scale to large core counts and speculation windows, including a new execution model, speculation-aware hardware task management, selective aborts, and scalable ordered commits.We evaluate Swarm on graph analytics, simulation, and database benchmarks. At 64 cores, Swarm achieves 51-122× speedups over a single-core system, and outperforms software-only parallel algorithms by 3-18×.

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Section: Background On Hw Support For Speculative Parallelismmentioning

confidence: 99%

Section: Background On Hw Support For Speculative Parallelismmentioning

confidence: 99%

Section: Speculative Execution and Versioningmentioning

confidence: 99%

Section: Additional Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A scalable architecture for ordered parallelism

Jeffrey¹,

Subramanian²,

Yan³

et al. 2015

Proceedings of the 48th International Symposium on Microarchitecture

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Full runtime polyhedral optimizing loop transformations with the generation, instantiation, and scheduling of code‐bones

Caamaño

Selva

Clauss

et al. 2017

Concurrency and Computation

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Summary In this paper, we present a new runtime code generation technique for speculative loop optimization and parallelization. The main benefit of this technique, compared to previous approaches, is to enable advanced optimizing loop transformations at runtime with an acceptable time overhead. The loop transformations that may be applied are those handled by the polyhedral model. The proposed code generation strategy is based on the generation of “code‐bones” at compile‐time, which are parametrized code snippets either dedicated to speculation management or to computations of the original target program. These code‐bones are then instantiated and assembled at runtime to constitute the speculatively optimized code, as soon as an optimizing polyhedral transformation has been determined. Their granularity threshold is sufficient to apply any polyhedral transformation, while still enabling fast runtime code generation. This approach has been implemented in the speculative loop parallelizing framework APOLLO.

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GbA: A graph‐based thread partition approach in speculative multithreading

Zhao

2017

Concurrency and Computation

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SummarySpeculative multithreading is an effective technique to automatically parallelize sequential programs. Conventional thread partition approaches primarily include heuristic rule–based (HR‐based) and machine learning–based. Heuristic rule–based approaches are effective to parallelize one type of programs and can seldom obtain the respective optimal partitions for different programs, and existing machine learning–based approaches usually use vector‐based characterization to represent a program, but easily ignore control information among basic blocks and partitions along other paths except the critical path. This paper proposes a novel graph‐based thread partition approach to overcome these 2 bottlenecks. Our approach characterizes programs with graphs, integrating feature and control informations, extracting good partition scheme successfully, and also applies a machine‐learning algorithm to predict partition for unseen programs. Prophet, which consists of an automatic parallelization compiler and a multicore simulator, evaluates the performance of multithreaded programs. Experiment results reveal that our approach delivers a maximum performance improvement of about 55.49% on an 8 core than HR‐based approach and a maximum 97.67% performance improvement over HR‐based partition for SPEC2000 benchmarks. This result suggests that graph‐based thread partition approach is effective for thread partition in speculative multithreading.

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A scalable approach to thread-level speculation

Cited by 109 publications

References 28 publications

A scalable architecture for ordered parallelism

A scalable architecture for ordered parallelism

Full runtime polyhedral optimizing loop transformations with the generation, instantiation, and scheduling of code‐bones

GbA: A graph‐based thread partition approach in speculative multithreading

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