Trading Off Performance for Energy in Linear Algebra Operations with Applications in Control Theory
We analyze the performance-power-energy balance of a conventional Intel Xeon multicore processor and two low-power architectures -an Intel Atom processor and a system with a quad-core ARM Cortex A9+NVIDIA Quadro 1000M- using a high performance implementation of Gauss-Jordan elimination (GJE) for matrix inversion. The blocked version of this algorithm employed in the experimental evaluation mostly comprises matrix-matrix products, so that the results from the evaluation carry beyond the simple matrix inversion and are representative for a wide variety of dense linear algebra operations/codes.
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| Main Authors: | , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Centro Latinoamericano de Estudios en Informática
2014
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| Online Access: | http://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002014000100004 |
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| Summary: | We analyze the performance-power-energy balance of a conventional Intel Xeon multicore processor and two low-power architectures -an Intel Atom processor and a system with a quad-core ARM Cortex A9+NVIDIA Quadro 1000M- using a high performance implementation of Gauss-Jordan elimination (GJE) for matrix inversion. The blocked version of this algorithm employed in the experimental evaluation mostly comprises matrix-matrix products, so that the results from the evaluation carry beyond the simple matrix inversion and are representative for a wide variety of dense linear algebra operations/codes. |
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