GPU-Accelerated Video Compression at Industrial Scale

We present Project Chimera, a novel GPU-native video compression service architecture that achieves 42x speed improvement over CPU-based solutions while maintaining equivalent perceptual quality. Our system demonstrates 77% GPU encoder utilization under concurrent load, processes 25,000+ videos daily per GPU, and reduces energy consumption by 37%.

We detail the architectural innovations enabling this performance: hot-reloadable containerization, intelligent quality targeting via VMAF, adaptive scene detection, and industrial-scale job orchestration. Comprehensive benchmarking across multiple quality levels reveals superior efficiency across the entire performance-quality frontier.

This work establishes GPU acceleration as the dominant paradigm for production video processing infrastructure, with 95% cost reduction compared to cloud services and 37% energy efficiency gains while maintaining 99.6% quality parity.