Peking University and DeepSeek have open-sourced DSpark, an inference acceleration framework for large language models. It uses a semi-autoregressive architecture and confidence-based scheduling to reduce latency and computing waste in high-concurrency scenarios. Tests show DSpark outperforms Eagle3 and DFlash, especially in long-sequence tasks. Deployed in DeepSeek-V4, the full code is on GitHub.