Data Sieving for Scalable Real-Time Multichannel Nanopore Sensing
This paper introduces "Data Sieving," a GPU-accelerated framework that enables scalable, real-time multichannel nanopore sensing by filtering continuous high-bandwidth streams to store only molecular event data, thereby reducing storage requirements by up to 98% while supporting autonomous closed-loop actuation for long-duration experiments.