Efficient compositing strategies for automotive HMI systems

Simon Gansel, Stephan Schnitzer, Riccardo Cecolin, Frank Dürr, K. Rothermel, Christian Maihöfer
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引用次数: 2

Abstract

The relevance of graphical functions in vehicular applications has increased significantly during the last years. Modern cars are equipped with multiple displays used by different applications such as speedometer, navigation system, or media players. The rendered output of the applications is stored in so-called off-screen buffers and then bitblitted to the screen buffer at the respective window sizes and positions. To guarantee the visibility of the potentially overlapping windows, the compositing has to match the z-order of the windows. To this end, two common compositing strategies Tile compositing and Full compositing are used, each having performance issues depending on how windows overlap. Since automotive embedded platforms are restricted in power consumption, installation space, and hardware cost, their performance is limited which effectuates the need for highly efficient bitblitting. In order to increase the performance in compositing the windows, we propose Hybrid Compositing which predicts the required bitblitting time and chooses the most efficient strategy for each pair of overlapping windows. Using various scenarios we show that our approach is faster than the other strategies. In addition, we propose CacheHybrid Compositing which reduces the CPU execution time of our approach by up to 66 %. In case of an automotive scenario we show that our optimized approach saves up to 51% bitblitting time compared to existing approaches.
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汽车人机界面系统的高效合成策略
在过去几年中,图形功能在车辆应用中的相关性显著增加。现代汽车配备了多种显示器,用于不同的应用,如速度计、导航系统或媒体播放器。应用程序的呈现输出存储在所谓的屏幕外缓冲区中,然后按各自的窗口大小和位置将其比特化到屏幕缓冲区中。为了保证潜在重叠窗口的可见性,合成必须匹配窗口的z轴顺序。为此,我们使用了两种常见的合成策略:Tile合成和Full合成,这两种策略都有性能问题,具体取决于窗口重叠的方式。由于汽车嵌入式平台在功耗、安装空间和硬件成本方面受到限制,因此其性能受到限制,从而实现了对高效比特化的需求。为了提高窗口合成的性能,我们提出了混合合成,预测所需的比特化时间,并为每对重叠窗口选择最有效的策略。通过使用不同的场景,我们证明了我们的方法比其他策略更快。此外,我们提出了CacheHybrid合成,它将我们的方法的CPU执行时间减少了66%。在汽车场景中,与现有方法相比,我们的优化方法节省了51%的比特化时间。
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