A method of parallel data processing optimization on a hardware platform comprising at least one computing unit comprising a plurality of processing units able to execute a plurality of executable tasks in parallel, wherein the data set to be processed is broken down into data subsets, a same sequence of operations being carried out on each data subset, characterized in that it comprises the following steps: - obtaining (50, 52) the maximum number of data subsets to be processed by a same sequence of operations, and a maximum number of tasks executable in parallel by a computing unit of the hardware platform, - determining at least two processing divisions Di, each processing division corresponding to the division of the data set into a number of groups of data, and assigning at least one executable task, able to execute said sequence of operations, to each data subset of said group of data, the total number of executable tasks per data group being less than or equal to said maximum number of tasks, - obtaining a program including programming code instructions implementing said processing division, - obtaining a value of an execution performance measurement associated with the execution of said program on said hardware platform, - selecting (60, 62) the processing division making it possible to obtain an optimal measuring value according to a predetermined criterion, and - obtaining information making it possible to generate programming code instructions implementing said selected processing division, comprising, after the step for obtaining a program including programming code instructions implementing a processing division, the following steps: - executing said program on said hardware platform a predetermined number of times and storing the execution performance measurement value corresponding to each execution, and - calculating a statistic from the stored execution performance measurement values, and - storing said calculated statistic as execution performance measurement value associated with said processing division. - obtaining (50, 52) the maximum number of data subsets to be processed by a same sequence of operations, and a maximum number of tasks executable in parallel by a computing unit of the hardware platform, - determining at least two processing divisions Di, each processing division corresponding to the division of the data set into a number of groups of data, and assigning at least one executable task, able to execute said sequence of operations, to each data subset of said group of data, the total number of executable tasks per data group being less than or equal to said maximum number of tasks, - obtaining a program including programming code instructions implementing said processing division, - obtaining a value of an execution performance measurement associated with the execution of said program on said hardware platform, - selecting (60, 62) the processing division making it possible to obtain an optimal measuring value according to a predetermined criterion, and - obtaining information making it possible to generate programming code instructions implementing said selected processing division, - executing said program on said hardware platform a predetermined number of times and storing the execution performance measurement value corresponding to each execution, and - calculating a statistic from the stored execution performance measurement values, and - storing said calculated statistic as execution performance measurement value associated with said processing division.