Abstract
Trees are common data structures that are used in many programs and applications. In its simplest form, a binary tree can be used to store numbers in sorted manners. Kd-trees, render trees and abstract syntax trees are more sophisticated examples of tree structures. Furthermore, in functional programming algebraic data types are essentially tree structures as well. In several tree-based applications, a tree is constructed, and several traversals traverse the tree to perform different computations. Tree fusion is a transformation that targets combining and fusing different traversals that traverse the same tree and perform them together (ideally in one traversal). Traversal fusion has several performance benefits such as reducing the traversing overhead and the memory accesses, enhancing locality, and eliminating intermediate structures. Previous work has been done on fusion and was mostly successful either in specific domains or limited scopes. This work introduces novel techniques for performing fusion in both imperative and functional programming settings with a focus on generality. The new techniques target general traversals; minimizing the burden on programmers and increasing the coverage of the transformation. Furthermore, it exploits fusion opportunities that previous approaches do not, achieving significant speedups for a wider range of programs.
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