the semantics of future and its use in program optimization
The future annotations of MultiLisp provide a simple method for taming the implicit parallelism of functional programs. Past research concerning future s has focused on implementation issues. In this paper, we present a series of operational semantics for an idealized functional language with future s 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.
semantic future use program program optimization optimality annotation method parallel functional programming research implementation paper operational semantics functional languages analysis algorithm experience compilation