Optimistic Evaluation: An Adaptive Evaluation Strategy for Non-Strict Programs (2003) [8 citations — 1 self]
by
Robert Ennals
,
Simon Peyton Jones
In ICFP ’03: Proceedings of the eighth ACM SIGPLAN international conference on Functional programming
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@INPROCEEDINGS{Ennals03optimisticevaluation:,
author = {Robert Ennals and Simon Peyton Jones},
title = {Optimistic Evaluation: An Adaptive Evaluation Strategy for Non-Strict Programs},
booktitle = {In ICFP ’03: Proceedings of the eighth ACM SIGPLAN international conference on Functional programming},
year = {2003},
pages = {287--298},
publisher = {ACM Press}
}
author = {Robert Ennals and Simon Peyton Jones},
title = {Optimistic Evaluation: An Adaptive Evaluation Strategy for Non-Strict Programs},
booktitle = {In ICFP ’03: Proceedings of the eighth ACM SIGPLAN international conference on Functional programming},
year = {2003},
pages = {287--298},
publisher = {ACM Press}
}
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Abstract:
Lazy programs are beautiful, but they are slow because they build many thunks. Simple measurements show that most of these thunks are unnecessary: they are in fact always evaluated, or are always cheap. In this paper we describe Optimistic Evaluation --- an evaluation strategy that exploits this observation. Optimistic Evaluation complements compile-time analyses with run-time experiments: it evaluates a thunk speculatively, but has an abortion mechanism to back out if it makes a bad choice. A run-time adaption mechanism records expressions found to be unsuitable for speculative evaluation, and arranges for them to be evaluated more lazily in the future.
