Scipediacontent: Scipediacontent moved page Draft Content 361376386 to Reynaud et al 2015a

2021-02-02T02:42:33Z

Scipediacontent moved page Draft Content 361376386 to Reynaud et al 2015a

Scipediacontent: Created page with " == Abstract == International audience; ADAS (Advanced Driver Assistance Systems) algorithms increasingly use heavy image processing operations. To embed this type of algorit..."

2021-02-02T02:42:29Z

Created page with " == Abstract == International audience; ADAS (Advanced Driver Assistance Systems) algorithms increasingly use heavy image processing operations. To embed this type of algorit..."

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== Abstract ==

International audience; ADAS (Advanced Driver Assistance Systems) algorithms increasingly use heavy image processing operations. To embed this type of algorithms, semiconductor companies offer many heterogeneous architectures. These SoCs (System on Chip) are composed of different processing units, with different capabilities, and often with massively parallel computing unit. Due to the complexity of these SoCs, predicting if a given algorithm can be executed in real time on a given architecture is not trivial. In fact it is not a simple task for automotive industry actors to choose the most suited heterogeneous SoC for a given application. Moreover, embedding complex algorithms on these systems remains a difficult task due to heterogeneity, it is not easy to decide how to allocate parts of a given algorithm on the different computing units of a given SoC. In order to help automotive industry in embedding algorithms on heterogeneous architectures, we propose a novel approach to predict performances of image processing algorithms applicable on different types of computing units. Our methodology is able to predict a more or less wide interval of execution time with a degree of confidence using only high level description of algorithms, and a few characteristics of computing units.

== Original document ==

The different versions of the original document can be found in:

* [https://hal.archives-ouvertes.fr/hal-01240121/file/RSaussard_HPCC2015.pdf https://hal.archives-ouvertes.fr/hal-01240121/file/RSaussard_HPCC2015.pdf]

* [http://xplorestaging.ieee.org/ielx7/7335977/7336120/07336166.pdf?arnumber=7336166 http://xplorestaging.ieee.org/ielx7/7335977/7336120/07336166.pdf?arnumber=7336166],
: [http://dx.doi.org/10.1109/hpcc-css-icess.2015.95 http://dx.doi.org/10.1109/hpcc-css-icess.2015.95]

* [https://dblp.uni-trier.de/db/conf/hpcc/hpcc2015.html#SaussardBVR15 https://dblp.uni-trier.de/db/conf/hpcc/hpcc2015.html#SaussardBVR15],
: [https://ieeexplore.ieee.org/document/7336166 https://ieeexplore.ieee.org/document/7336166],
: [https://dl.acm.org/citation.cfm?id=2860713.2861790 https://dl.acm.org/citation.cfm?id=2860713.2861790],
: [https://doi.org/10.1109/HPCC-CSS-ICESS.2015.95 https://doi.org/10.1109/HPCC-CSS-ICESS.2015.95],
: [https://academic.microsoft.com/#/detail/2174408454 https://academic.microsoft.com/#/detail/2174408454]

* [https://hal.archives-ouvertes.fr/hal-01240121 https://hal.archives-ouvertes.fr/hal-01240121],
: [https://hal.archives-ouvertes.fr/hal-01240121/document https://hal.archives-ouvertes.fr/hal-01240121/document],
: [https://hal.archives-ouvertes.fr/hal-01240121/file/RSaussard_HPCC2015.pdf https://hal.archives-ouvertes.fr/hal-01240121/file/RSaussard_HPCC2015.pdf]

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Reynaud et al 2015a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 361376386 to Reynaud et al 2015a

Scipediacontent: Created page with " == Abstract == International audience; ADAS (Advanced Driver Assistance Systems) algorithms increasingly use heavy image processing operations. To embed this type of algorit..."