processing the signature quadratic form distance on many-core gpu architectures
The Signature Quadratic Form Distance on feature signatures represents a flexible distance-based similarity model for effective content-based multimedia retrieval. Although metric indexing approaches are able to speed up query processing by two orders of magnitude, their applicability to large-scale multimedia databases containing billions of images is still a challenging issue. In this paper, we propose the utilization of GPUs for efficient query processing with the Signature Quadratic Form Distance. We show how to process multiple distance computations in parallel and demonstrate efficient query processing by comparing many-core GPU with multi-core CPU implementations.
quadratic form distance many-core gpu similarity search