Affiliation:
1. Philipps-Universität Marburg
Abstract
If the result of an expensive computation is invalidated by a small change to the input, the old result should be updated incrementally instead of reexecuting the whole computation. We incrementalize programs through their
derivative
. A derivative maps changes in the program's input directly to changes in the program's output, without reexecuting the original program. We present a program transformation taking programs to their derivatives, which is fully static and automatic, supports first-class functions, and produces derivatives amenable to standard optimization.
We prove the program transformation correct in Agda for a family of simply-typed λ-calculi, parameterized by base types and primitives. A precise interface specifies what is required to incrementalize the chosen primitives.
We investigate performance by a case study: We implement in Scala the program transformation, a plugin and improve performance of a nontrivial program by orders of magnitude.
Funder
European Research Council
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design,Software
Reference23 articles.
1. Self-adjusting computation
2. Adaptive functional programming
3. An experimental analysis of self-adjusting computation
4. Traceable data types for self-adjusting computation
5. Agda Development Team. The Agda Wiki. http://wiki.portal.chalmers.se/agda/ 2013. Accessed on 2013-10-30. Agda Development Team. The Agda Wiki. http://wiki.portal.chalmers.se/agda/ 2013. Accessed on 2013-10-30.
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