@inproceedings{b6c62dc6fefb45cfbae52fb5d298ffb9,
title = "CPP-taskflow: Fast task-based parallel programming using modern C++",
abstract = "In this paper we introduce Cpp-Taskflow, a new C++ tasking library to help developers quickly write parallel programs using task dependency graphs. Cpp-Taskflow leverages the power of modern C++ and task-based approaches to enable efficient implementations of parallel decomposition strategies. Our programming model can quickly handle not only traditional loop-level parallelism, but also irregular patterns such as graph algorithms, incremental flows, and dynamic data structures. Compared with existing libraries, Cpp-Taskflow is more cost efficient in performance scaling and software integration. We have evaluated Cpp-Taskflow on both micro-benchmarks and real-world applications with million-scale tasking. In a machine learning example, Cpp-Taskflow achieved 1.5-2.7× less coding complexity and 14-38% speed-up over two industrial-strength libraries OpenMP Tasking and Intel Threading Building Blocks (TBB).",
author = "Huang, {Tsung Wei} and Lin, {Chun Xun} and Guannan Guo and Martin Wong",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE; 33rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2019 ; Conference date: 20-05-2019 Through 24-05-2019",
year = "2019",
month = may,
doi = "10.1109/IPDPS.2019.00105",
language = "English (US)",
series = "Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "974--983",
booktitle = "Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019",
address = "United States",
}