Permanent link to this recordhttp://hdl.handle.net/10754/656693
MetadataShow full item record
AbstractWe 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 an 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 possibly hardware accelerator-equipped systems. 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%) 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.
The following license files are associated with this item: