ACCELERATION OF RANKING ALGORITHMS USING A GRAPHICS PROCESSING UNIT

摘要

Methods, computer systems, and computer-readable media for accelerating a learning-to-rank algorithm using a central processing unit (CPU) and a graphics processing unit (GPU) are provided. The GPU processes document pairs created by the CPU in parallel to generate a lambda-gradient value and a weight for each document. The CPU builds a regression tree for the documents. The GPU is utilized to accelerate this process by constructing histograms of feature values, wherein the address of bins collecting the same feature value are shifted during the construction of the histogram. The output of the regression tree is a score for each document which is used to rank or order the document on a search engine results page.