ParT: An Asynchronous Parallel Abstraction for Speculative Pipeline Computations

Fernandez-Reyes, Kiko; Clarke, Dave; McCain, Daniel S.

doi:10.29007/j7j6

Cited by 3 publications

(5 citation statements)

References 2 publications

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“…Complete configurations can be typed by adding extra conditions to ensure that all futures in Γ have a future configuration, there is a one-to-one correspondence between tasks/chains and unfulfilled futures, and dependencies between tasks are acyclic. These definitions have been omitted and are similar to those found in our earlier work [9].…”

Section: Static Semanticsmentioning

confidence: 96%

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Forward to a Promising Future

Fernandez-Reyes

Clarke

Castegren

et al. 2018

Lecture Notes in Computer Science

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Abstract. In many actor-based programming models, 1 asynchronous method calls communicate their results using futures, where the fulfilment occurs under-the-hood. Promises play a similar role to futures, except that they must be explicitly created and explicitly fulfilled; this makes promises more flexible than futures, though promises lack fulfilment guarantees: they can be fulfilled once, multiple times or not at all. Unfortunately, futures are too rigid to exploit many available concurrent and parallel patterns. For instance, many computations block on a future to get its result only to return that result immediately (to fulfil their own future). To make futures more flexible, we explore a construct, forward, that delegates the responsibility for fulfilling the current implicit future to another computation. Forward reduces synchronisation and gives futures promise-like capabilities. This paper presents a formalisation of the forward construct, defined in a high-level source language, and a compilation strategy from the high-level language to a low-level, promised-based target language. The translation is shown to preserve semantics. Based on this foundation, we describe the implementation of forward in the parallel, actor-based language Encore, 2 which compiles to C.

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Section: Static Semanticsmentioning

confidence: 96%

“…The proof of progress requires that there is no deadlock, which follows as there is no cyclic dependency between tasks [9].…”

Section: Static Semanticsmentioning

confidence: 99%

Forward to a Promising Future

Fernandez-Reyes

Clarke

Castegren

et al. 2018

Lecture Notes in Computer Science

Self Cite

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“…ParT [8] in the Encore language, provides the notion of arrays of futures that distributes data as different futures, but does not allow to synchronize parts of data as a single future. It can be used to implement speculative parallelism or barriers gathering a set of results.…”

Section: Related Workmentioning

confidence: 99%

Distributed futures for efficient data transfer between parallel processes

Leca

Suijlen

Henrio

et al. 2020

Proceedings of the 35th Annual ACM Symposium on Applied Computing

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This paper defines distributed futures, a construct that provides at the same time a data container similar to a distributed vector, and a single synchronization entity that behaves similarly to a standard future. This simple construct makes it easy to program a composition, in a task-parallel way, of several massively data-parallel tasks. The approach is implemented and evaluated in the context of a bulk synchronous parallel (BSP) active object framework. CCS CONCEPTS• Software and its engineering → Parallel programming languages; Concurrent programming structures.

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“…Several extensions to the active object model enable controlled parallelism inside active objects [12,8,2]. Multi-active objects is an extension of ASP [12] where the programmer can declare that several requests can run in parallel on the same object.…”

Section: Active Objects and Actorsmentioning

confidence: 99%

“…This solution relies on the correctness of program annotation to prevent data-races but provides efficient data-parallelism inside active objects. Parallel combinators of Encore [8] also enable some form of restricted parallelism inside an active object, mostly dedicated to the coordination of parallel tasks. A set of parallel operators is proposed to the programmer, but different messages still have to be handled by different active objects.…”

Section: Active Objects and Actorsmentioning

confidence: 99%

Active Objects for Coordinating BSP Computations (Short Paper)

Hains¹,

Henrio²,

Leca³

et al. 2018

Lecture Notes in Computer Science

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Among the programming models for parallel and distributed computing, one can identify two important families. The programming models adapted to data-parallelism, where a set of coordinated processes perform a computation by splitting the input data; and coordination languages able to express complex coordination patterns and rich interactions between processing entities. This article takes two successful programming models belonging to the two categories and puts them together into an effective programming model. More precisely, we investigate the use of active objects to coordinate BSP processes. We choose two paradigms that both enforce the absence of data-races, one of the major sources of error in parallel programming. This article explains why we believe such a model is interesting and provides a formal semantics integrating the notions of the two programming paradigms in a coherent and effective manner.

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ParT: An Asynchronous Parallel Abstraction for Speculative Pipeline Computations

Cited by 3 publications

References 2 publications

Forward to a Promising Future

Forward to a Promising Future

Distributed futures for efficient data transfer between parallel processes

Active Objects for Coordinating BSP Computations (Short Paper)

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