PublisherAssociation for Computing Machinery (ACM)
Rights accessRestricted access - publisher's policy
Dependency-aware task-based parallel programming models have proven to be successful for developing application software for multicore-based computer architectures.
Here we consider the problem of scheduling tasks not only with respect to their inter-dependencies, but also with respect to their usage of resources such as memory and bandwidth. At the software level, this is achieved by user annotations of the task resource consumption. In the run-time system, the annotations are translated into scheduling constraints. Experimental results demonstrating performance gains both for model examples and real applications are presented.
CitationTillenius, M. [et al.]. Resource-aware task scheduling. A: Workshop on Parallel Programming and Run-time Management Techniques for Many-core Architectures. "ACM Transactions on Embedded Computing Systems (TECS), Volume 14, Issue 1, January 2015". Berlin: Association for Computing Machinery (ACM), 2013.
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