视频生成DeepSeek时刻！清华&生数开源框架提速200倍，一周斩获2k Star

Core Insights - The article discusses the launch of TurboDiffusion, an open-source framework developed by Tsinghua University's TSAIL team and Shenshu Technology, which significantly accelerates video generation, reducing the time required to generate videos from minutes to seconds [1][3][7]. Group 1: Technological Breakthrough - TurboDiffusion marks a pivotal shift from traditional video rendering and waiting to real-time generation, addressing the high inference latency that has limited the practical use of video generation models [3][7]. - The framework achieves approximately 200 times acceleration in generating high-quality videos, allowing a 5-second 720p video to be produced in just 24 seconds on a single RTX 5090 GPU [26][43]. - The technology employs four core techniques: mixed attention acceleration, efficient step distillation, and W8A8 linear layer quantization, which collectively enhance video generation efficiency without compromising quality [13][20][21]. Group 2: Implementation and Performance - Mixed attention acceleration includes SageAttention and Sparse-Linear Attention (SLA), which optimize attention mechanisms for faster processing [14][17]. - Efficient step distillation reduces the number of sampling steps required for video generation from 100 to as few as 3 or 4, maintaining high video quality [20]. - The W8A8 linear layer quantization compresses model size by about 50%, utilizing INT8 Tensor Cores for faster linear layer computations [21]. Group 3: Industry Impact - TurboDiffusion's introduction lowers the computational barrier for high-end video creation, making it accessible to individual creators using consumer-grade GPUs [51]. - The framework enables near real-time video generation, enhancing creative exploration by allowing instant feedback on adjustments to prompts [52]. - The advancements in video generation technology, including TurboDiffusion, are expected to facilitate the development of applications requiring immediate feedback, such as AI video live streaming and AR/VR content rendering [52].