Content-aware compression of data using window-based selection from multiple prediction functions

Abstract

Data compression with window-based selection from multiple prediction functions is provided. A predefined default predictor and a plurality of other predictors are applied to a floating point number to generate a plurality of predictions. A compression metric over a collection of floating point numbers is evaluated for the default predictor and the plurality of other predictors. Based on the compression metric, (i) the floating point number is encoded using the predefined default predictor, or (ii) the collection of floating point numbers is encoded using one of the other predictors. Stored indexes indicate which predictor was used for the encoding. A set of predictors out of a larger set of predictors can be determined for a specific data set based on a performance-based ranking. The default predictor and the alternate predictors can be represented as ensembles of predictors. Decompression involves evaluating which predictor was used for the encoding and optionally, whether an ensemble was used for the encoding.