Embodiments described herein provide a configurable heterogeneous Artificial Intelligence (AI) processor comprising at least two different architectural types of computation units, a storage unit and a controller. Each of the computation units has a respective task queue. The controller is configured to partition a computation graph of a neural network into a plurality of computation subtasks and distribute the computation subtasks to the task queues of the computation units. The controller is also configured to set a dependency among the computation subtasks, synchronize the computation subtasks according to the set dependency, and control access to data involved in the computation subtasks. Different application tasks are processed by uniformly managing and scheduling the various architectural types of computation units in an on-chip heterogeneous manner, so that the AI processor can flexibly adapt to different application scenarios.