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An Optimised Flow for Futures: From Theory to Practice

Abstract : A future is an entity representing the result of an ongoing computation. A synchronisation with a "get" operation blocks the caller until the computation is over, to return the corresponding value. When a computation in charge of fulfilling a future delegates part of its processing to another task, mainstream languages return nested futures, and several "get" operations are needed to retrieve the computed value (we call such futures "control-flow futures"). Several approaches were proposed to tackle this issues: the "forward" construct, that allows the programmer to make delegation explicit and avoid nested futures, and "data-flow explicit futures" which natively collapse nested futures into plain futures. This paper supports the claim that data-flow explicit futures form a powerful set of language primitives, on top of which other approaches can be built. We prove the equivalence, in the context of data-flow explicit futures, between the "forward" construct and classical "return" from functions. The proof relies on a branching bisimulation between a program using "forward" and its "return" counterpart. This result allows language designers to consider "forward" as an optimisation directive rather than as a language primitive. Following the principles of the Godot system, we provide a library implementation of control-flow futures, based on data-flow explicit futures implemented in the compiler. This small library supports the claim that the implementation of classical futures based on data-flow ones is easier than the opposite. Our benchmarks show the viability of the approach from a performance point of view.
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Contributor : Ludovic Henrio Connect in order to contact the contributor
Submitted on : Monday, November 22, 2021 - 3:19:00 PM
Last modification on : Tuesday, October 25, 2022 - 4:25:11 PM


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Nicolas Chappe, Ludovic Henrio, Amaury Maillé, Matthieu Moy, Hadrien Renaud. An Optimised Flow for Futures: From Theory to Practice. The Art, Science, and Engineering of Programming, 2021, 6 (1), pp.1-41. ⟨10.22152/⟩. ⟨hal-03440766⟩



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