1. A system comprising: a plurality of central processing units; a memory; and a controller, embedded in a processing component, the controller coupled to the memory and coupled to the plurality of central processing units, wherein the controller is operable to direct selection of a sequential execution mode or one of a plurality of parallel execution modes with respect to said plurality of central processing units, wherein the controller is further operable to: generate respective definition characteristics for each task of a plurality of tasks, each definition characteristic comprising a task feature set including, for each respective task, at least one of: a number of instructions in the task, a number of task parameters associated with the task, a time of execution of the task, an amount of memory usage by the task, and a number of instructions in the respective task; and an input feature set including, for each respective task, at least one of: a number of inputs to the task, a size of an input to the task, a type of an input to the task, and a dimension of input data to the task; establish a plurality of definition pairs that map the definition characteristics to execution modes using a neural network trained by supervised machine learning based training, and responsive to the generated definition characteristics for each task, execute adaptive selection of the execution mode to be used by the central processing units for each task on-the-fly while the central processing units are running the tasks.