We describe the quad rope data structure, a representation of immutable two-dimensional arrays that avoids many of the performance pitfalls of plain C-style two-dimensional arrays. Our motivation is that, for end-user development in high-level declarative programming languages, it is impractical to let users choose between different array-like data structures. Instead, one should use the same, somewhat performance-robust, representation for every programming task. Quad ropes roughly retain array efficiency, as long as programmers express their programs using high-level constructs. Moreover, they allow for fast concatenation and dynamic task-based parallelism and are well suited to represent sparse arrays. We describe their operational semantics and evaluate the performance of individual functions on quad ropes as well as declarative algorithms that use our quad rope implementation.
Title of host publication
Proceedings of the 4th ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming : ARRAY 2017
ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming - Barcelona, Spain Duration: 18 Jun 2017 → 23 Jun 2017 Conference number: 4 http://pldi17.sigplan.org/track/array-2017
ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming
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