Book
Cloud-native GPU-enabled architecture for parallel video encoding
| العنوان: | Cloud-native GPU-enabled architecture for parallel video encoding |
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| المؤلفون: | Salcedo-Navarro, Andoni, Peña-Ortiz, Raúl, Claver Iborra, José Manuel, Garcia-Pineda, Miguel, Gutiérrez-Aguado, Juan |
| بيانات النشر: | Springer |
| سنة النشر: | 2024 |
| المجموعة: | Universitat de València: Roderic - Repositorio de contenido libre |
| مصطلحات موضوعية: | GPU, Cloud Computing, Kubernetes, Video Encoding, HTTP Adaptive Streaming, UNESCO::CIENCIAS TECNOLÓGICAS |
| الوصف: | Multimedia streaming has become an essential aspect of contemporary life and the ever-growing demand for high-quality streaming has fostered the development of new video codecs and improvements in content delivery. Cloud computing, particularly cloud architectures, has played a pivotal role in this evolution, offering dynamic resource allocation, parallel execution, and automatic scaling—critical features for HTTP Adaptive Streaming applications. This paper presents two specialized containers designed for video encoding (using two implementations of H264: x264 that encodes in the CPU and H264 NVENC that also uses the GPU). These containers are deployed on a Kubernetes cluster with four GPUs. The experiments focus on the performance and resource consumption of the encoder containers under different Kubernetes cluster and replica configurations. The best setup shows a 12.7% reduction in encoding time for x264 and a 15.98% for H264 NVENC compared to the other configurations considered. Besides, the encoding time of H264 NVENC is reduced by a 3.29 factor compared to x264. To test the behavior in realistic scenarios, four videos were encoded at five different resolutions. The mean encoding time per segment is reduced by a 3.75 factor when using H264 NVENC compared to x264. These results hold significant implications for livestreaming applications, particularly for low-latency use cases. |
| نوع الوثيقة: | book part |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | Lecture Notes in Computer Science; PID2021-126209OB-I00; https://hdl.handle.net/10550/100761; https://link.springer.com/chapter/10.1007/978-3-031-69583-4_23 |
| DOI: | 10.1007/978-3-031-69583-4_23 |
| الاتاحة: | https://hdl.handle.net/10550/100761 https://doi.org/10.1007/978-3-031-69583-4_23 https://link.springer.com/chapter/10.1007/978-3-031-69583-4_23 |
| Rights: | open access |
| رقم الانضمام: | edsbas.56F43D26 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1007/978-3-031-69583-4_23 |
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