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NSFDirectorate for Technology, Innovation, and Partnerships

POSE: Phase I: Toward a Task-Parallel Programming Ecosystem for Modern Scientific Computing

Completed
Institution
University of Wisconsin-Madison, WI
Principal investigator
Tsung-Wei Huang
Funding
$299K
Duration
2023–2024
Open portfolio

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Abstract

Open-source software systems designed for task-parallel programming have become central to a wide range of modern scientific computing applications, such as machine learning and quantum computing. While decades of research has yielded many open-source task-parallel programming systems, most of them are led by a handful of developers and their impacts do not sustain in the long run. To overcome this challenge, this project proposes scoping activities to establish a route to a long-term sustainable ecosystem for task-parallel programming. These activities build atop the open-source software, Taskflow, a high-performance task-parallel system to streamline the building of complex scientific computing applications. This project starts by discovering an ecosystem based on three increasing applications of Taskflow, quantum computing, circuit design automation, and multimedia. The discovery effort consists of designing showcase software products and organizing workshops to pursue the optimal ecosystem for Taskflow. Then, the project designs a series of developer training programs to engage potential content contributors who can help develop and maintain Taskflow in a community-driven fashion. Finally, the project establishes a transparent and publicly visible governance model to formalize the decision-making process of Taskflow for various elements, including technical contributions, partnership, and security policies. This project lays the foundation for Taskflow to transition to a robust and sustainable system asset for the scientific computing community to quickly respond to emerging parallelism using scalable task-based approaches. Many scoping activities in this project can instill confidence in commercial adoption of Taskflow and grow its partnership with other open-source scientific computing projects to further broaden its impact and enhance sustainability. Also, results produced in this project can be used in classrooms to renovate existing learning materials for high-performance computing and software practice, engaging a diverse group of students in open-source development. The project website is available at https://taskflow.github.io/ which contains the latest news, source code, step-by-step learning materials, and benchmarks. The authors are committed to developing and maintaining the project in the long term. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Directorate for Technology, Innovation, and PartnershipsPOSEecosystemprogrammingscientific computingquantum computingopen-sourcecomputinglearning materialscomputing applications

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