Trainer of many core systems for adaptive resource control

Abstract

Disclosed herein is a trainer of a many core system comprising a plurality of cores for controlling resource utilization within the many core system, wherein the trainer comprises a controller configured to cause a task scheduler to add a first synthetic variable load () to at least one task thread comprising at least one task and to schedule the at least one task thread; cause a generic probe element () to set a plurality of probes configured to measure a real time requirement at a respective plurality of points within an execution of the at least one task thread; cause a training element () to calculate a real time slack measurement constant (RS) value based on the worst case timing for each of the plurality of probes and to select at least one of the plurality of probes, wherein the selected at least one probe has a worst case RS value, wherein the training element is further configured to calculate a system load constant (SL) value based on the worst case RS value; and to cause a resource manager to adjust at least one system parameter based on the at least one probe having the worst case RS value. Also disclosed is a method of a trainer and a computer program product.