Abstract: Methods and apparatus are provided for content-aware compression of data using multiple prediction functions.

Abstract: Multiple parallel prediction functions are employed for content-aware data compression. An exemplary method comprises obtaining a floating point number comprising a sign, an exponent at a given base and a significand having a length; applying a plurality of distinct prediction algorithms to the floating point number to generate a corresponding plurality of predictions; selecting a given one of the plurality of distinct prediction algorithms for the floating point number by evaluating a compression metric applied to the plurality of predictions; and encoding the floating point number by encoding the exponent and the length as a single code using a residual generated by the selected prediction algorithm. A disambiguation index optionally identifies the selected prediction algorithm among a set of prediction algorithms that potentially generated the selected prediction.

Abstract: Methods and apparatus are provided for content-aware compression of data using selection from multiple weighted prediction functions. An exemplary method comprises obtaining a floating point number; applying a plurality of distinct prediction algorithms to the floating point number to generate a corresponding plurality of predictions; selecting at least one of the predictions for the floating point number based on combination weights for the plurality of distinct prediction algorithms, wherein the combination weights are based only on prior samples of the floating point numbers; and encoding the floating point number by encoding, as a single code, the exponent and the length of a residual generated by the distinct prediction algorithm associated with the selected at least one prediction. The combination weights are optionally updated for subsequent floating point numbers.