First-class schedules and virtual maps

Mirani, Rajiv; Hudak, Paul

doi:10.1145/224164.224185

Cited by 11 publications

(7 citation statements)

References 21 publications

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“…This ability enables programs where the details of what is to be computed are separate from how the computation is to be performed. PML does not provide evaluation strategies directly, but there is a similar approach called first-class monadic schedules (FCMS) (Mirani & Hudak 1995) that can be readily encoded on top of pvals. FCMS offers some additional powerful features, such as the ability to define processor topologies and to determine on which processor each thread executes.…”

Section: Related Workmentioning

confidence: 99%

Implicitly threaded parallelism in Manticore

Fluet¹,

Rainey²,

Reppy³

et al. 2010

J. Funct. Prog.

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The increasing availability of commodity multicore processors is making parallel computing available to the masses. Traditional parallel languages are largely intended for large-scale scientific computing and tend not to be well-suited to programming the applications one typically finds on a desktop system. Thus we need new parallel-language designs that address a broader spectrum of applications. In this paper, we present Manticore, a language for building parallel applications on commodity multicore hardware including a diverse collection of parallel constructs for different granularities of work. We focus on the implicitly-threaded parallel constructs in our high-level functional language. We concentrate on those elements that distinguish our design from related ones, namely, a novel parallel binding form, a nondeterministic parallel case form, and exceptions in the presence of data parallelism. These features differentiate the present work from related work on functional data parallel language designs, which has focused largely on parallel problems with regular structure and the compiler transformations -most notably, flattening -that make such designs feasible. We describe our implementation strategies and present some detailed examples utilizing various mechanisms of our language.

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Section: Related Workmentioning

confidence: 99%

Implicitly threaded parallelism in Manticore

Fluet¹,

Rainey²,

Reppy³

et al. 2010

J. Funct. Prog.

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show abstract

“…Some non-functional approaches are also covered. The approach that is most closely related to our work is that using first-class schedules (Mirani and Hudak, 1995), described in Section 6.4.…”

Section: Related Workmentioning

confidence: 99%

“…In its simplest form, this can be simply a set of annotations that specify process creation, etc. More sophisticated systems, such as Caliban (Kelly, 1989), or first-class schedules (Mirani and Hudak, 1995) support normal functional expressions as part of the process control language.…”

Section: Parallel Language Extensionsmentioning

confidence: 99%

Algorithm + strategy = parallelism

et al. 1998

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The process of writing large parallel programs is complicated by the need to specify both the parallel behaviour of the program and the algorithm that is to be used to compute its result. This paper introduces evaluation strategies: lazy higher-order functions that control the parallel evaluation of non-strict functional languages. Using evaluation strategies, it is possible to achieve a clean separation between algorithmic and behavioural code. The result is enhanced clarity and shorter parallel programs. Evaluation strategies are a very general concept: this paper shows how they can be used to model a wide range of commonly used programming paradigms, including divide-and-conquer parallelism, pipeline parallelism, producer/consumer parallelism, and data-oriented parallelism. Because they are based on unrestricted higher-order functions, they can also capture irregular parallel structures. Evaluation strategies are not just of theoretical interest: they have evolved out of our experience in parallelising several large-scale parallel applications, where they have proved invaluable in helping to manage the complexities of parallel behaviour. Some of these applications are described in detail here. The largest application we have studied to date, Lolita, is a 40,000 line natural language engineering system. Initial results show that for these programs we can achieve acceptable parallel performance, for relatively little programming effort.

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“…A schedule [Mirani and Hudak 1995] is a partial order on the evaluation of expressions in a program. In this article the default evaluation strategy is • R. Mirani and P. Hudak assumed to be weak head normal order (lazy) evaluation, which is completely sequential (i.e., the partial order on reduction steps is completely linear).…”

Section: Schedulesmentioning

confidence: 99%

First-class monadic schedules

Mirani

Hudak

2004

ACM Trans. Program. Lang. Syst.

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Parallel functional languages often use meta-linguistic annotations to provide control over parallel evaluation. In this paper we explore a flexible mechanism to control when an expression is evaluated: first-class monadic schedules. We discuss the advantages of using such first-class values over traditional annotation-based systems. In particular, it is often desirable to make decisions about the operational behavior of parallel programs depending on the dynamic state of the system. For example, we may want to measure the system load before deciding to evaluate expressions in parallel. For this purpose, we show how monads can be used to access dynamic system parameters in a referentially transparent manner (up to termination).As a mechanism to reason about schedules, we present a set of algebraic properties that any implementation of schedules must satisfy. We also describe an implementation that translates schedules into a dialect of Scheme extended with futures. We prove that this implementation satisfies the given set of algebraic properties, and give performance results for a parallel solution to the n-body problem using the Barnes-Hut method.Although our ideas were developed specifically for nonstrict functional languages such as Haskell, we briefly discuss how they can be used with strict functional languages and imperative languages as well.

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First-class schedules and virtual maps

Abstract: Explicitly parallel functional languages typically use metalinguistics annotations to provide control over parallel evaluation.

Cited by 11 publications

References 21 publications

Implicitly threaded parallelism in Manticore

Implicitly threaded parallelism in Manticore

Algorithm + strategy = parallelism

First-class monadic schedules

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