Video streaming became an undivided part of the Internet. To efficiently utilize the limited network bandwidth it is essential to encode the video content. However, encoding is a computationally intensive task, involving high-performance resources provided by private infrastructures or public clouds. Public clouds, such as Amazon EC2, provide a large portfolio of services and instances optimized for specific purposes and budgets. The majority of Amazon instances use x86 processors, such as Intel Xeon or AMD EPYC. However, following the recent trends in computer architecture, Amazon introduced Arm-based instances that promise up to 40% better cost-performance ratio than comparable x86 instances for specific workloads. We evaluate in this paper the video encoding performance of x86 and Arm instances of four instance families using the latest FFmpeg version and two video codecs. We examine the impact of the encoding parameters, such as different presets and bitrates, on the time and cost for encoding. Our experiments reveal that Arm instances show high time and cost-saving potential of up to 33.63% for specific bitrates and presets, especially for the x264 codec. However, the x86 instances are more general and achieve low encoding times, regardless of the codec.

中文翻译：

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在哪里编码：x86 和基于 Arm 的 Amazon EC2 实例的性能分析

视频流成为互联网不可分割的一部分。为了有效利用有限的网络带宽，必须对视频内容进行编码。然而，编码是一项计算密集型任务，涉及私有基础设施或公共云提供的高性能资源。公共云（例如 Amazon EC2）提供了大量针对特定目的和预算进行了优化的服务和实例组合。大多数 Amazon 实例使用 x86 处理器，例如 Intel Xeon 或 AMD EPYC。然而，随着计算机架构的最新趋势，亚马逊推出了基于 Arm 的实例，对于特定工作负载，该实例承诺比同类 x86 实例的性价比高 40%。我们在本文中使用最新的 FFmpeg 版本和两个视频编解码器评估了四个实例系列的 x86 和 Arm 实例的视频编码性能。我们检查了编码参数（例如不同的预设和比特率）对编码时间和成本的影响。我们的实验表明，对于特定比特率和预设，尤其是 x264 编解码器，Arm 实例显示出高达 33.63% 的高时间和成本节省潜力。但是，无论使用何种编解码器，x86 实例都更通用并且编码时间较短。特别是对于 x264 编解码器。但是，无论使用何种编解码器，x86 实例都更通用并且编码时间较短。特别是对于 x264 编解码器。但是，无论使用何种编解码器，x86 实例都更通用并且编码时间较短。