The present application relates to a kind of intelligent
inference framework optimization method based on real-time
operating system and
multicore CPU, belong to real-time
operating system field.The method of the present application includes: task splitting and core allocation:
inference task is divided according to the way of tile, each core is responsible for
processing the
inference task of a tile;Each tile will be allocated to idle core and be processed in parallel;Real-time monitoring and dynamic adjustment:
system will monitor the load condition of each core in real time, and dynamically adjust the allocation of task according to the idleness of core and the complexity of task;Through work stealing technique, if the load of a core is low, it will obtain task from other core to balance the load;Priority and task scheduling: when
processing the task with higher real-time requirement, it is preferentially allocated to high-priority core.The present application effectively improves the inference efficiency and
resource utilization of
system.