Paged Attention and Virtual Memory for LLM Inference

Key Points

• The research investigates methods to enhance efficiency in large language model (LLM) inference.
• Developed a novel paged attention mechanism
• Integrated virtual memory approaches
• Compared performance with traditional inference methods
• Showed significant improvements in memory usage
• Achieved faster inference times compared to standard techniques
• Increased scalability of LLM applications

Abstract