This program is tentative and subject to change.
Reductions combine collections of input values with an associative and often commutative operator to produce collections of results. When the same input value contributes to multiple outputs, there is an opportunity to reuse partial results, enabling reduction simplification. Simplification often produces a program with lower asymptotic complexity. Typical compiler optimizations yield, at best, a constant fold speedup, but complexity improvement from, say, cubic to quadratic complexity yields unbounded speedup for sufficiently large problems. It is well known that reductions in polyhedral programs may be simplified automatically, but previous methods cannot exploit all available reuse. This paper resolves this long-standing open problem, thereby attaining minimal asymptotic complexity in the simplified program. We propose extensions to prior work on simplification to support any independent commutative reduction. At the heart of our approach is piece-wise simplification, the notion that we can split an arbitrary reduction into pieces and then independently simplify each piece. However, the difficulty of using such piece-wise transformations is that they typically involve an infinite number of choices. We give constructive proofs to deal with this and select a finite number of pieces for simplification.
This program is tentative and subject to change.
Wed 22 JanDisplayed time zone: Mountain Time (US & Canada) change
10:40 - 12:00 | |||
10:40 20mTalk | Maximal Simplification of Polyhedral Reductions POPL Louis Narmour Colorado State University, Tomofumi Yuki , Sanjay Rajopadhye Colorado State University | ||
11:00 20mTalk | Program Analysis via Multiple Context Free Language Reachability POPL Giovanna Kobus Conrado Hong Kong University of Science and Technology, Adam Husted Kjelstrøm Aarhus University, Jaco van de Pol Aarhus University, Andreas Pavlogiannis Aarhus University | ||
11:20 20mTalk | The Best of Abstract Interpretations POPL Pre-print | ||
11:40 20mTalk | An Incremental Algorithm for Algebraic Program Analysis POPL Chenyu Zhou University of Southern California, Yuzhou Fang University of Southern California, Jingbo Wang Purdue University, Chao Wang University of Southern California |