Performance evaluation of Kvazaar HEVC intra encoder on Xeon Phi many-core processor

Koivula, Ari; Viitanen, Marko; Lemmetti, Ari; Vanne, Jarno; Hämäläinen, Timo D.

doi:10.1109/globalsip.2015.7418398

Cited by 12 publications

(7 citation statements)

References 10 publications

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“…All experimentations are performed on one core of the EmETXe-i87M0 platform from Arbor Technologies based on an Intel Core i5-4402E processor at 1.6 GHz. The used Hevc software encoder is the real time Kvazaar [13,14,30] in All Intra (AI) configuration. Since the configuration aims to be real-time, from [16], the Rate-Distortion Optimisation Quantization (RDOQ) [10] and the Intra transform skipping [15] features are disabled.…”

Section: Methodsmentioning

confidence: 99%

On predicting the HEVC intra quad-tree partitioning with tunable energy and rate-distortion

Mercat

Arrestier

Pelcat

et al. 2018

J Real-Time Image Proc

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Future evolutions of the Internet of Things (IoT) are likely to boost mobile video demand to an unprecedented level. A large number of battery-powered systems will then integrate an High Efficiency Video Coding (Hevc) codec, implementing the latest video encoding standard from MPEG, and these systems will need to be energy efficient. Constraining the energy consumption of Hevc encoders is a challenging task, especially for embedded applications based on software encoders. The most efficient approach to manage the energy consumption of an Hevc encoder consists in optimizing the quad-tree partitioning and balance compression efficiency and energy consumption. The quad-tree partitioning splits the image into encoding units of variable sizes. The optimal size for a unit is content dependent and affects the encoding efficiency. Finding this optimal repartition is complex and the energy required by the so-called Rate-Distortion Optimization (RDO) process dominates the encoder energy consumption. For the purpose of budgeting the energy consumption of a real-time Hevc encoder, we propose in this paper a variance-aware quad-tree prediction that limits the energetic cost of the RDO process. The predictor is moreover adjustable by two parameters, (∆, ∆), offering a tradeoff between energetic gains and compression efficiency. Experimental results show that the proposed energy reduction scheme is able to reduce the energy consumption of a real-time Hevc encoder by 45% to 62% for a bit rate increase of respectively 0.49% and 3.4%. Moreover, the flexibility offered by parameters (∆, ∆) opens new opportunities for energy-aware encoding management.

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Section: Methodsmentioning

confidence: 99%

On predicting the HEVC intra quad-tree partitioning with tunable energy and rate-distortion

Mercat

Arrestier

Pelcat

et al. 2018

J Real-Time Image Proc

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show abstract

“…All experimentations are performed on one core of the embedded EmETXe-i87M0 platform from Arbor Technologies based on an Intel Core i5-4402E processor at 1.6 GHz. The studied Hevc software encoder is Kvazaar [17,18,41] in AI configuration. Each of the tested configurations is used to encode 100 frames of 4 highresolution (1080p) reference video sequences: Cactus, Bas-ketballDrive, BQTerrace and ParkScene with QPs 22, 27, 32, 37 [4].…”

Section: Methodsmentioning

confidence: 99%

Smart search space reduction for approximate computing: A low energy HEVC encoder case study

Mercat

Bonnot

Pelcat

et al. 2017

Journal of Systems Architecture

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International audienceThe approximate computing paradigm provides methods to optimize algorithms while considering both application quality of service and computational complexity. Approximate computing can be applied at different levels of abstraction, from algorithm level to application level. Approximate computing at algorithm level reduces the computational complexity by approximating or skipping computational blocks. A number of applications in the signal and image processing domain integrate algorithms based on discrete optimization techniques. These techniques minimize a cost function by exploring an application parameter search space. In this paper, a new methodology is proposed that exploits the computation-skipping approximate computing concept. The methodology, named Smart Search Space Reduction(SSSR), explores at design time the Pareto relationship between computational complexity and application quality. At run time, an approximation manager can then early select a good candidate configuration. SSSR reduces the run time search space and, in turn, reduces computational complexity. An efficient SSSR technique adjusts at design time the configuration selectivity while selecting at run time the most suitable functions to skip. The real time High Efficiency Video CodingHEVC encoder in All Intra(AI) profile is used as a case study to illustrate the benefits of SSSR. In this application, two discrete optimizations are performed. They explore different coding parameters and select the values leading to the minimal cost in terms of a tradeoff between bitrate, quality and computational energy by acting on both the HEVC coding-tree partitioning and the intra-modes. Combining two SSSRs iterations on this use case, the energy consumption is reduced by up to 77%. Moreover, the combination of the two SSSRs iterations in comparison to using only one reduces the BD-BR bitrate/quality metric by 4% for the same energy consumption. © 201

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“…First we project the omnidirectional video of each VP onto a 3 × 2 compacted cube-map baseball as illustrated in Figure 2. For each tile set-up (no tile, 3 × 2, and 6 × 4 tiles), we used the open-source Kvazaar [19] Table 2: Information about the users: sex, age, number of switching event, median angular velocity. The median angular velocity is ether computed globally, two seconds before a switch event, two seconds after a switch event or in the period between two switch events.…”

Section: Test-bedmentioning

confidence: 99%

Dynamic adaptive streaming for multi-viewpoint omnidirectional videos

Corbillon

Simone

Simon

et al. 2018

Proceedings of the 9th ACM Multimedia Systems Conference

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Full immersion inside a Virtual Reality (VR) scene requires six Degrees of Freedom (6DoF) applications where the user is allowed to perform translational and rotational movements within the virtual space. The implementation of 6DoF applications is however still an open question. In this paper we study a multi-viewpoint (MVP) 360-degree video streaming system, where a scene is simultaneously captured by multiple omnidirectional video cameras. The user can only switch positions to predefined viewpoints (VPs). We focus on the new challenges that are introduced by adaptive MVP 360-degree video streaming. We introduce several options for video encoding with existing technologies, such as High Efficiency Video Coding (HEVC) and for the implementation of VP switching. We model three video-segment download strategies for an adaptive streaming client into Mixed Integer Linear Programming (MILP) problems: an omniscient download scheduler; one where the client proactively downloads all VPs to guarantee fast VP switch; one where the client reacts to the user's navigation pattern. We recorded a one MVP 360-degree video with three VPs, implemented a mobile MVP 360-degree video player, and recorded the viewing patterns of multiple users navigating the content. We solved the adaptive streaming optimization problems on this video considering the collected navigation traces. The results emphasize the gains obtained by using tiles in terms of objective quality of the delivered content. They also emphasize the importance of performing further study on VP switching prediction to reduce the bandwidth consumption and to measure the impact of VP switching delay on the subjective Quality of Experience (QoE). Part of the research published in this paper was conducted while Francesca De Simone was affiliated to the LTS4 at EPFL. The authors thanks the Swisscom Innovation Lab for providing the omnidirectional cameras used to record the content and Meryem Wehbe who implemented the MVP 360-degree player used to collect the navigation patterns used in this study.

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Performance evaluation of Kvazaar HEVC intra encoder on Xeon Phi many-core processor

Cited by 12 publications

References 10 publications

On predicting the HEVC intra quad-tree partitioning with tunable energy and rate-distortion

On predicting the HEVC intra quad-tree partitioning with tunable energy and rate-distortion

Smart search space reduction for approximate computing: A low energy HEVC encoder case study

Dynamic adaptive streaming for multi-viewpoint omnidirectional videos

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