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vbench: Benchmarking Video Transcoding in the Cloud

Published:19 March 2018Publication History
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Abstract

This paper presents vbench, a publicly available benchmark for cloud video services. We are the first study, to the best of our knowledge, to characterize the emerging video-as-a-service workload. Unlike prior video processing benchmarks, vbench's videos are algorithmically selected to represent a large commercial corpus of millions of videos. Reflecting the complex infrastructure that processes and hosts these videos, vbench includes carefully constructed metrics and baselines. The combination of validated corpus, baselines, and metrics reveal nuanced tradeoffs between speed, quality, and compression. We demonstrate the importance of video selection with a microarchitectural study of cache, branch, and SIMD behavior. vbench reveals trends from the commercial corpus that are not visible in other video corpuses. Our experiments with GPUs under vbench's scoring scenarios reveal that context is critical: GPUs are well suited for live-streaming, while for video-on-demand shift costs from compute to storage and network. Counterintuitively, they are not viable for popular videos, for which highly compressed, high quality copies are required. We instead find that popular videos are currently well-served by the current trajectory of software encoders.

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            • Published in

              cover image ACM SIGPLAN Notices
              ACM SIGPLAN Notices  Volume 53, Issue 2
              ASPLOS '18
              February 2018
              809 pages
              ISSN:0362-1340
              EISSN:1558-1160
              DOI:10.1145/3296957
              Issue’s Table of Contents
              • cover image ACM Conferences
                ASPLOS '18: Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems
                March 2018
                827 pages
                ISBN:9781450349116
                DOI:10.1145/3173162

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 19 March 2018

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