Evaluation of Hardware-based Video Encoders on Modern GPUs for UHD Live-Streaming

2025-11-23

AI Summary

Real-time 4K/8K ultra-high-definition (UHD) live streaming demands efficient, high-quality video encoding with strict latency and power constraints, yet comprehensive cross-platform, cross-standard hardware encoder evaluations remain scarce. Method: We systematically benchmark modern GPU (NVIDIA, Intel) and Snapdragon SoC hardware encoders alongside software encoders using PSNR, SSIM, and VMAF. We conduct the first generation-spanning RD analysis of HEVC, VP9, AV1, and VVC across hardware and software implementations, measuring encoding speed, quality, and power consumption, while calibrating bitrate requirements to match YouTube’s transcoding quality tiers. Results: Modern hardware encoders achieve subjective quality on par with software encoders at real-time speeds; architectural improvements yield substantial speed gains but marginal RD performance gains across generations; platform-specific bitrate thresholds for achieving target perceptual quality are empirically identified. This work provides reproducible, multi-dimensional benchmarks—spanning quality, speed, and energy efficiency—to guide codec selection for UHD live streaming deployments.

Technology Category

• Machine Learning: Hardware-aware ML
• Computer Vision: Computational Photography, Image & Video Synthesis
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Economics, Online Markets and Human Computation: Economics and fairness of platforms and recommendation systems

Abstract

Many GPUs have incorporated hardware-accelerated video encoders, which allow video encoding tasks to be offloaded from the main CPU and provide higher power efficiency. Over the years, many new video codecs such as H.265/HEVC, VP9, and AV1 were added to the latest GPU boards. Recently, the rise of live video content such as VTuber, game live-streaming, and live event broadcasts, drives the demand for high-efficiency hardware encoders in the GPUs to tackle these real-time video encoding tasks, especially at higher resolutions such as 4K/8K UHD. In this paper, RD performance, encoding speed, as well as power consumption of hardware encoders in several generations of NVIDIA, Intel GPUs as well as Qualcomm Snapdragon Mobile SoCs were evaluated and compared to the software counterparts, including the latest H.266/VVC codec, using several metrics including PSNR, SSIM, and machine-learning based VMAF. The results show that modern GPU hardware encoders can match the RD performance of software encoders in real-time encoding scenarios, and while encoding speed increased in newer hardware, there is mostly negligible RD performance improvement between hardware generations. Finally, the bitrate required for each hardware encoder to match YouTube transcoding quality was also calculated.

Problem

• Evaluating hardware video encoders on modern GPUs for UHD live-streaming applications
• Comparing encoding performance across GPU generations and mobile SoC platforms
• Assessing bitrate requirements to match YouTube's transcoding quality standards

Innovation

• Hardware-accelerated video encoders on modern GPUs
• Evaluated encoding performance using PSNR SSIM VMAF
• Compared hardware software encoders for UHD live-streaming