Keywords:API, programming interface, parallel programming, shared memory, distributed memory, parallel operator, data structure
AbstractEffectively implementing scientific algorithms in distributed memory parallel applications is a difficult task for domain scientists, as evident by the large number of domain-specific languages and libraries available today attempting to facilitate the process. However, they usually provide a closed set of parallel patterns and are not open for extension without vast modifications to the underlying system. In this work, we present the AllScale API, a programming interface for developing distributed memory parallel applications with the ease of shared memory programming models. The AllScale API is closed for a modification but open for an extension, allowing new user-defined parallel patterns and data structures to be implemented based on existing core primitives and therefore fully supported in the AllScale framework. Focusing on high-level functionality directly offered to application developers, we present the design advantages of such an API design, detail some of its specifications and evaluate it using three real-world use cases. Our results show that AllScale decreases the complexity of implementing scientific applications for distributed memory while attaining comparable or higher performance compared to MPI reference implementations.
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How to Cite
Gschwandtner, P., Jordan, H., Thoman, P., & Fahringer, T. (2021). AllScale API. COMPUTING AND INFORMATICS, 39(4), 808–837. https://doi.org/10.31577/cai_2020_4_808
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