Tsung-Wei Huang, Chun-Xun Lin, Guannan Guo, Martin D. F. Wong
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引用次数: 51
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).