Abstract
The work proposes ffMDF, a lightweight dynamic run-time support able to achieve high performance in the execution of dense linear algebra kernels on shared-cache multi-core. ffMDF implements a dynamic macro-data-flow interpreter processing DAG graphs generated on-the-fly out of standard numeric kernel code. The experimental results demonstrate that the performance obtained using ffMDF on both fine-grain and coarse-grain problems is comparable with or even better than that achieved by de-facto standard solutions (notably PLASMA library), which use separate run-time supports specifically optimised for different computational grains on modern multi-core.
Original language | English |
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Title of host publication | Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Networks, PDCN 2014 |
Publisher | ACTA Press |
Pages | 283-292 |
DOIs | |
Publication status | Published - 2014 |
Externally published | Yes |
Event | 12th IASTED International Conference on Parallel and Distributed Computing and Networks, PDCN 2014 - , Austria Duration: 17 Feb 2014 → 19 Feb 2014 |
Conference
Conference | 12th IASTED International Conference on Parallel and Distributed Computing and Networks, PDCN 2014 |
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Country/Territory | Austria |
Period | 17/02/14 → 19/02/14 |