@inproceedings{e94e467f0b474c2c8385dcc30496e8c9,
title = "Lazy decomposition: A novel technique to control parallel task granularity",
abstract = "This paper introduces a new mechanism for the exposure of large grain parallelism. The scheme performs lazy task creation; inlining all tasks provisionally and extracting parallelism from the inlined information later on demand. However, unlike other mechanisms, the further task demand is satisfied by the next evaluation stream rather than retrospectively reversing the inlining decision of the current stream. The scheme is called lazy decomposition because decomposition itself is throttled rather than just the extraction of a task. Lazy decomposition makes the serial section clearly separated from the parallel section in an evaluation tree for a particular function, and this allows the serial section to adopt a sequential algorithm. The performance improvement is significant in divide-and-conquer applications by adoption of sequential algorithms.",
author = "Suntae Hwang and Hojung Cha",
note = "Publisher Copyright: {\textcopyright} 1997 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 3rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 1997 ; Conference date: 10-12-1997 Through 12-12-1997",
year = "1997",
doi = "10.1109/ICAPP.1997.651511",
language = "English",
series = "1997 3rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 1997",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "427--434",
editor = "Wanlei Zhou and Andrzej Goscinski and Michael Hobbs",
booktitle = "1997 3rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 1997",
address = "United States",
}