The semantics of future and its use in program optimization

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Abstract
The future annotations of MultiLisp provide a simple method for taming the implicit parallelism of functional programs. Past research concerning futures has focused on implementation issues. In this paper, we present a series of operational semantics for an idealized functional language with futures with varying degrees of intensionality. We develop a set-based analysis algorithm from the most intensional semantics, and use that algorithm to perform touch optimization on programs. Experiments with the Gambit compiler indicates that this optimization substantially reduces program execution times.

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