Dnotitia Brings Dedicated Vector Silicon to Server Scale at AI Infra Summit 2026

Dnotitia’s VDPU ASIC samples are back from the fab. This moves dedicated vector silicon closer to market. The company’s FPGA evaluations showed a four-card VDPU server delivered up to 5.77x the vector-search throughput of a dual-socket CPU server. It also reduced host CPU use by 92% and memory by 73% in a 4,096-dimensional multimodal workload.

This focus on retrieval processing is critical for Asian AI infrastructure. Agentic AI and RAG workloads are shifting bottlenecks from model compute. Companies like South Korea’s Naver or Kakao, heavily invested in AI services, could see significant efficiency gains. They need to free up CPU capacity and GPU HBM for core application and model execution.

The test for Dnotitia is whether its ASIC can hit the targeted 10x performance. ASIC-based evaluations begin in Q4 2026. Broader support for vector libraries beyond FAISS, Milvus, and hnswlib will determine its market penetration. Asian data center operators will watch these performance figures closely.