SC20 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Warwick Data Store: A Data Structure Abstraction Library


Workshop:PMBS20: The 11th International Workshop on Performance Modeling, Benchmarking and Simulation of High-Performance Computer Systems

Authors: Richard Kirk (University of Warwick); Martin Nolten, Robert Kevis, Timothy Law, and Satheesh Maheswaran (Atomic Weapons Establishment (AWE), UK); Steven Wright (University of York); Seimon Powell (Atomic Weapons Establishment (AWE), UK); Gihan Mudalige (University of Warwick); and Stephen Jarvis (University of Birmingham)


Abstract: With the increasing complexity of memory architectures and scientific applications, developing data structures that are performant, portable, scalable, and support developer productivity, is a challenging task. In this paper, we present Warwick Data Store (WDS), a lightweight and extensible C++ template library designed to manage these complexities and allow rapid prototyping.

WDS is designed to abstract details of the underlying data structures away from the user, thus easing application development and optimization. We show that using WDS does not significantly impact achieved performance across a variety of different scientific benchmarks and proxy-applications, compilers, and different architectures. The overheads are largely below 30% for smaller problems, with the overhead deceasing to below 10% when using larger problems. This shows that the library does not significantly impact the performance, while providing additional functionality to data structures, and the ability to optimize data structures without changing the application code.





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