IEEE eScience 2021: Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2 Instances

17th IEEE eScience 2021
20-23 September 2021 // Innsbruck, Austria // Online Conference
Conference Website


Roland Matha´∗, Dragi Kimovski*, Anatoliy Zabrovskiy*‡, Christian Timmerer*†, Radu Prodan*
Institute of Information Technology (ITEC), University of Klagenfurt, Austria*
Bitmovin, Klagenfurt, Austria†
Petrozavodsk State University, Petrozavodsk, Russia‡

Abstract: Video streaming became an undivided part of the Internet. To efficiently utilise 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’s 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.

Index Terms—Amazon EC2, Arm instances, AVC, Cloud computing, FFmpeg, Graviton2, HEVC, Performance analysis, Video encoding.

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