System and method for generating a parallel processing approximation model
OwnerKevin D. Howardinventor
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Abstract
A parallel processing approximation model is automatically generated via a method including generating a time complexity search table including a plurality of columns and rows, each header of the column defining a polynomial which defines the algorithmic time complexity or overhead time complexity, and each row within the column defining the respective polynomial for a plurality of dataset divisions or size multiplications. The method further includes generating a comparison column and determining an approximation column having the highest algorithmic time complexity values that do not exceed the time complexity comparison column.
Claims14
A method for generating a prediction of parallel processing of an algorithm having a dataset capable of being subdivided, using a system comprising a processor and memory, the method comprising the steps of:
- generating a time complexity search table comprising a plurality of columns and a plurality of rows, each column comprising an approximation header defining a polynomial which defines a time complexity of the algorithm and each row of each column defining the time complexity value of the respective polynomial for a plurality of dataset multiplications;
- generating a time complexity comparison column defining plurality of values of the wall clock time required to execute the algorithm for the plurality of dataset multiplications;
- determining a time complexity approximation column within the time complexity search table defining the column having the highest time complexity values that do not exceed the values of the time complexity comparison column;
- storing the header of the time complexity approximation column within the memory;
- and
- generating a time complexity determination model output comprising the header of the time complexity approximation column stored within the memory.
A method for generating a prediction of algorithmic overhead of parallel processing of an algorithm having a dataset capable of being subdivided, using a system comprising a processor and memory, the method comprising:
- generating an overhead time complexity search table comprising a plurality of columns and a plurality of rows, each column comprising an overhead time complexity approximation header defining a polynomial which defines an overhead of the algorithm and each row of each column defining the overhead time complexity value of the respective polynomial for a plurality of dataset divisions;
- generating an overhead time complexity comparison column defining plurality of values of the additional overhead wall clock time required to execute the algorithm for the plurality of dataset divisions;
- determining an overhead approximation column within the overhead time complexity search table defining the column having the highest algorithmic overhead time complexity values that do not exceed the values of the overhead time complexity comparison column;
- storing the header of the overhead approximation column within the memory;
- and
- generating an overhead time complexity approximation model output comprising the header of the overhead time complexity approximation column stored within the memory.
Dependencies are inferred from the claim text.