מושגי ליבה
PipeRAG introduces pipeline parallelism, flexible retrieval intervals, and performance modeling to improve efficiency in retrieval-augmented generation, achieving significant speedups without compromising quality.
תקציר
PipeRAG presents a novel approach to enhance the efficiency of retrieval-augmented generation by integrating pipeline parallelism, flexible retrieval intervals, and performance modeling. The evaluation demonstrates up to a 2.6× speedup in end-to-end generation latency while maintaining or improving generation quality. By co-designing algorithms with underlying systems, PipeRAG showcases promising results for future RAG systems.
Key points:
- Introduction of PipeRAG for efficient retrieval-augmented generation.
- Utilization of pipeline parallelism, flexible retrieval intervals, and performance modeling.
- Evaluation showing up to 2.6× speedup in end-to-end generation latency.
- Importance of algorithm-system co-design for optimizing RAG systems.
סטטיסטיקה
Our evaluation shows that PipeRAG achieves up to 2.6× speedup in end-to-end generation latency while improving generation quality.
PipeRAG integrates pipeline parallelism to enable concurrent retrieval and generation processes.
Flexible retrieval intervals are used to maximize the efficiency of pipeline parallelism.
A performance model is employed to automatically balance retrieval quality and latency based on the generation states and underlying hardware.