Computer Processing and Outcome Prediction Systems and Methods

A method of determining non-linear speedup of one or more Time-Affecting Linear Pathways (TALPs) executing on multiple processing elements (PEs), comprising:

• calculating a scaled processing time of the one or more TALPs given associated individual input variable attributes that affect a number of loop iterations of one or more looping structures, and evenly dividing input variable attribute values that affect loop iterations by a number of PEs;
• converting the scaled processing time of the one or more TALPs into one or more scaled time complexity functions, which is equivalent to speedup;
• separating out a static processing time generated at least by executing and timing one or more static loops;
• defining a maximum number of possible PEs for a given input dataset as scaled input variable attribute values that affect the number of loop iterations;
• and
• finding a maximum speedup using a minimum detected processing time that corresponds to the maximum number of possible PEs and a minimum number of possible loop iterations for a TALP.

A method of generating one or more time-affecting linear pathways (TALPs), comprising:

• creating a source values table and a target values table for each input dataset attribute that affects processing time of one or more multiple attribute TALPs by repeatedly selecting and varying a different input dataset attribute value while holding unselected input dataset attribute values constant;
• comparing one or more scaled monotonic processing time values of the source values table to associated time values of the target values table;
• creating one or more final polynomials based on the comparison;
• determining a relationship between one or more input variable attributes values that affect the processing time of the one or more multiple attribute TALPs by examining respective loop structure relationships;
• combining the one or more final polynomials, from each of the one or more input variable attribute values that affect the processing time of the one or more multiple attribute TALPs, into a single polynomial using the determined relationships between all input variable attribute values that affect the processing time of the one or more multiple attribute TALPs;
• selecting one or more TALPs to be executed given a set of input variable attribute values;
• and
• calculating a predictive processing time of one or more TALPs given the set of input variable attribute values.

A system of generating one or more time-affecting linear pathways (TALPs), comprising:

• a memory;
• and
• a processor operatively coupled with the memory, wherein the processor is configured to execute program code to:
• create a source values table and a target values table for each input dataset attribute that affects processing time of one or more multiple attribute TALPs by repeatedly selecting and varying a different input dataset attribute value while holding unselected input dataset attribute values constant;
• compare one or more scaled monotonic processing time values of the source values table to associated time values of the target values table;
• create one or more final polynomials based on the comparison;
• determine a relationship between one or more input variable attributes values that affect the processing time of the one or more multiple attribute TALPs by examining respective loop structure relationships;
• combine the one or more final polynomials, from each of the one or more input variable attribute values that affect the processing time of the one or more multiple attribute TALPs, into a single polynomial using the determined relationships between all input variable attribute values that affect the processing time of the one or more multiple attribute TALPs;
• select one or more TALPs to be executed given a set of input variable attribute values;
• and
• calculate a predictive processing time of one or more TALPs given the set of input variable attribute values.