Abstraction Layer For Standardizing APIs of Task-Based Engines

We introduce AL4SAN , a lightweight library for abstracting the APIs of task-based runtime engines. AL4SAN unifies the expression of tasks and their data dependencies. It supports various dynamic runtime systems relying on compiler technology and user-defined APIs. It enables a single application to...

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Veröffentlicht in:IEEE transactions on parallel and distributed systems Jg. 31; H. 11; S. 2482 - 2495
Hauptverfasser: Alomairy, Rabab, Ltaief, Hatem, Abduljabbar, Mustafa, Keyes, David
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.11.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
abstraction layer
Accelerators
Algorithms
API standardization
Co-design
Distributed memory
dynamic runtime systems
Eigenvalues
Engines
Hardware
Interoperability
Libraries
LLVM compiler infrastructure
Productivity
Programming
Runtime
runtime interoperability
Task analysis
Task-based programming model
user productivity
Workloads
ISSN:1045-9219, 1558-2183
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Zusammenfassung:We introduce AL4SAN , a lightweight library for abstracting the APIs of task-based runtime engines. AL4SAN unifies the expression of tasks and their data dependencies. It supports various dynamic runtime systems relying on compiler technology and user-defined APIs. It enables a single application to employ different runtimes and their respective scheduling components, while providing user-obliviousness to the underlying hardware configurations. AL4SAN exposes common front-end APIs and connects to different back-end runtimes. Experiments on performance and overhead assessments are reported on various shared- and distributed-memory systems, possibly equipped with hardware accelerators. A range of workloads, from compute-bound to memory-bound regimes, are employed as proxies for current scientific applications. The low overhead (less than 10 percent) achieved using a variety of workloads enables AL4SAN to be deployed for fast development of task-based numerical algorithms. More interestingly, AL4SAN enables runtime interoperability by switching runtimes at runtime. Blending runtime systems permits to achieve a twofold speedup on a task-based generalized symmetric eigenvalue solver, relative to state-of-the-art implementations. The ultimate goal of AL4SAN is not to create a new runtime, but to strengthen co-design of existing runtimes/applications, while facilitating user productivity and code portability. The code of AL4SAN is freely available at https://github.com/ecrc/al4san , with extensions in progress.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2020.2992923