D-NOVA: In-Storage Retrieval Accelerator for RAG via Dual-Bound 3D NAND-Optimized Similarity Search
D-NOVA is a hardware-software co-designed in-storage retrieval accelerator that executes IVF-based hierarchical retrieval directly within NAND memory arrays. It introduces a Dual-Bound Tight Similarity Sensing (DTS) metric and a lightweight contrastive adapter to recover near-software recall. The system achieves up to 41.7x speedup and 71x energy efficiency over CPU baselines, and up to 12.13x higher throughput than prior in-storage RAG accelerators.
Why it matters: This work addresses the critical latency and energy bottleneck of dense vector retrieval in RAG by deeply embedding search into NAND memory, potentially enabling scalable and efficient retrieval for large-scale LLM applications.
Full story at: arXiv Information Retrieval ↗