Abstract: Software systems and methods convert algorithms and software codes into time affecting linear pathways (TALPs) via decomposition and convert paired Input/Output (I/O) datasets into TALPs via Value Complexity polynomials. Generated TALPs can be enhanced through merging with other TALPs. TALPs can be grouped by matching the outputs of the TALP-associated prediction polynomials with some set of given criteria into families and cross-families that are useful in a new type of software optimization that allows for output values of grouped TALPs to be modeled, pooled, discretized and optimized to enhance goals or meet user goals.

Abstract: Methods and systems for existing software applications to automatically take advantage of multicore computer systems outside of the conventional simultaneous processing of multiple applications and without performance problems from cache misses and mismatched task processing times are presented. Unlike other multicore optimization techniques, the present invention uses techniques that are applied to design graphs and work for scaled and standard speedup-based parallel processing. The methods and systems optimize software designs that are attached to code for maximum performance on multicore computer hardware by analyzing and modifying loop structures to produce a general parallel solution, not just simple loop unrolling.

Abstract: Software systems and methods convert algorithms and software codes into time affecting linear pathways (TALPs) via decomposition and convert paired Input/Output (I/O) datasets into TALPs via Value Complexity polynomials. Generated TALPs can be enhanced through merging with other TALPs. TALPs can be grouped by matching the outputs of the TALP-associated prediction polynomials with some set of given criteria into families and cross-families that are useful in a new type of software optimization that allows for output values of grouped TALPs to be modeled, pooled, discretized and optimized to enhance goals or meet user goals.

Abstract: Methods and systems for existing software applications to automatically take advantage of multicore computer systems outside of the conventional simultaneous processing of multiple applications and without performance problems from cache misses and mismatched task processing times are presented. Unlike other multicore optimization techniques, the present invention uses techniques that are applied to design graphs and work for scaled and standard speedup-based parallel processing. The methods and systems optimize software designs that are attached to code for maximum performance on multicore computer hardware by analyzing and modifying loop structures to produce a general parallel solution, not just simple loop unrolling.

Abstract: Software systems and methods convert algorithms and software codes into time affecting linear pathways (TALPs) via decomposition and convert paired Input/Output (I/O) datasets into TALPs via Value Complexity polynomials. Generated TALPs can be enhanced through merging with other TALPs. TALPs can be grouped by matching the outputs of the TALP-associated prediction polynomials with some set of given criteria into families and cross-families that are useful in a new type of software optimization that allows for output values of grouped TALPs to be modeled, pooled, discretized and optimized to enhance goals or meet user goals.

Abstract: A software enhancement and management system (E&M System) can include two ways to decompose existing software such that new functionality can be added: functional decomposition and time-affecting linear pathway (TALP) decomposition. Functional decomposition captures the inputs and outputs of the existing software's functions and attaches the new algorithmic constructs presented as other functions that receive the outputs of the existing software's functions. TALP decomposition allows for the generation of time-prediction polynomials that approximate time-complexity functions, speedup, and automatic dynamic loop-unrolling-based parallelization for each TALP.