high performance computing on graphics processing units: hgpu.org

Embedded devices and multimedia applications today generate unprecedented volumes of data which must be indexed and made searchable. As a result, similarity search has become a critical idiom for many modern data intensive applications in natural language processing (NLP), vision, and robotics. At its core, similarity search is implemented using k-nearest neighbors (kNN) where computation consists of highly parallel distance calculations and a global top-k sort. In contemporary von-Neumann architectures, kNN is bottlenecked by data movement limiting throughput and latency.