DSpark: Speculative decoding accelerates LLM inference [pdf]
DeepSeek has introduced the DSpark framework, a system designed to accelerate Large Language Model (LLM) inference using speculative decoding. This approach improves text generation speed by utilizing a smaller, faster draft model to propose potential tokens, which are subsequently verified in parallel by the primary target model. The DSpark framework optimizes coordination strategies and addresses key system bottlenecks to reduce overall latency and increase throughput for real-world high-concurrency production environments. The release has sparked significant community interest, drawing over 600 points of engagement on Hacker News. (source: https://github.com/deepseek-ai/DeepSpec/blob/main/DSpark_paper.pdf)