Scipediacontent: Scipediacontent moved page Draft Content 530556130 to Annavaram et al 2016a

2021-02-03T20:11:23Z

Scipediacontent moved page Draft Content 530556130 to Annavaram et al 2016a

Scipediacontent: Created page with " == Abstract == Graphical processing units (GPUs) are increasingly used to run a wide range of general purpose applications. Due to wide variation in application parallelism..."

2021-02-03T20:11:20Z

Created page with " == Abstract == Graphical processing units (GPUs) are increasingly used to run a wide range of general purpose applications. Due to wide variation in application parallelism..."

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== Abstract ==

Graphical processing units (GPUs) are increasingly used to run a wide range of general purpose applications. Due to wide variation in application parallelism and inherent application level inefficiencies, GPUs experience significant idle periods. In this work, we first show that significant fine-grain pipeline bubbles exist regardless of warp scheduling policies or workloads. We propose to convert these bubbles into energy saving opportunities using Origami. Origami consists of two components: Warp Folding and the Origami scheduler. With Warp Folding, warps are split into two half-warps which are issued in succession. Warp Folding leaves half of the execution lanes idle, which is then exploited to improve energy efficiency through power gating. Origami scheduler is a new warp scheduler that is cognizant of the Warp Folding process and tries to further extend the sleep times of idle execution lanes. By combining the two techniques Origami can save 49% and 46% of the leakage energy in the integer and floating point pipelines, respectively. These savings are better than or at least on-par with Warped-Gates, a prior power gating technique that power gates the entire cluster of execution lanes. But Origami achieves these energy savings without relying on forcing idleness on execution lanes, which leads to performance losses, as has been proposed in Warped-Gates. Hence, Origami is able to achieve these energy savings with virtually no performance overhead.

== Original document ==

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

* [http://dl.acm.org/ft_gateway.cfm?id=2926281&type=pdf http://dl.acm.org/ft_gateway.cfm?id=2926281&type=pdf]

* [https://dblp.uni-trier.de/db/conf/ics/ics2016.html#Abdel-Majeed0KA16 https://dblp.uni-trier.de/db/conf/ics/ics2016.html#Abdel-Majeed0KA16],
: [https://dl.acm.org/ft_gateway.cfm?id=2926281&type=pdf https://dl.acm.org/ft_gateway.cfm?id=2926281&type=pdf],
: [https://dl.acm.org/citation.cfm?id=2926281 https://dl.acm.org/citation.cfm?id=2926281],
: [https://dl.acm.org/citation.cfm?doid=2925426.2926281 https://dl.acm.org/citation.cfm?doid=2925426.2926281],
: [https://doi.org/10.1145/2925426.2926281 https://doi.org/10.1145/2925426.2926281],
: [https://core.ac.uk/display/103469887 https://core.ac.uk/display/103469887],
: [https://academic.microsoft.com/#/detail/2415201000 https://academic.microsoft.com/#/detail/2415201000]

* [https://dl.acm.org/doi/pdf/10.1145/2925426.2926281 https://dl.acm.org/doi/pdf/10.1145/2925426.2926281],
: [http://dx.doi.org/10.1145/2925426.2926281 http://dx.doi.org/10.1145/2925426.2926281] under the license http://www.acm.org/publications/policies/copyright_policy#Background

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Annavaram et al 2016a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 530556130 to Annavaram et al 2016a

Scipediacontent: Created page with " == Abstract == Graphical processing units (GPUs) are increasingly used to run a wide range of general purpose applications. Due to wide variation in application parallelism..."