Algorithm–HW Co-Design Framework for Accelerating Attention in Large-Context Scenarios (Cornell)


A new technical paper titled "LongSight: Compute-Enabled Memory to Accelerate Large-Context LLMs via Sparse Attention" was published by researchers at Cornell University. Abstract "Large input context windows in transformer-based LLMs help minimize hallucinations and improve output accuracy and personalization. However, as the context window grows, the attention phase increasingly dominates... » read more