Abstract:
A task scheduling method is applied to a heterogeneous multi-core processor system. The heterogeneous multi-core processor system has at least one first processor core and at least one second processor core. The task scheduling method includes: referring to task priorities of tasks of the heterogeneous processor cores to identify at least one first task of the tasks that belongs to a first priority task group, wherein each first task belonging to the first priority task group has a task priority not lower than task priorities of other tasks not belonging to the first priority task group; and dispatching at least one of the at least one first task to at least one run queue of at least one of the at least one first processor core.
Abstract:
A multi-core processor system and a method for assigning tasks are provided. The multi-core processor system includes a plurality of processor cores, configured to perform a plurality of tasks, and each of the tasks is in a respective one of a plurality of scheduling classes. The multi-core processor system further includes a task scheduler, configured to obtain first task assignment information about tasks in a first scheduling class assigned to the processor cores, obtain second task assignment information about tasks in one or more other scheduling classes assigned to the processor cores, and refer to the first task assignment information and the second task assignment information to assign a runnable task in the first scheduling class to one of the processor cores.
Abstract:
A switch interconnect is dynamically controlled at runtime to connect power sources to processing units in a multiprocessor system. Each power source is shareable by the processing units and each processing unit has a required voltage for processing a workload. When a system condition is detected at runtime, the switch interconnect is controlled to change a connection between at least one processing unit and a shared power source to maximize power efficiency. The shared power source is one of the power sources that supports multiple processing units having different required voltages.
Abstract:
A multi-cluster system having processor cores of different energy efficiency characteristics is configured to operate with high efficiency such that performance and power requirements can be satisfied. The system includes multiple processor cores in a hierarchy of groups. The hierarchy of groups includes: multiple level-1 groups, each level-1 group including one or more of processor cores having identical energy efficiency characteristics, and each level-1 group configured to be assigned tasks by a level-1 scheduler; one or more level-2 groups, each level-2 group including respective level-1 groups, the processor cores in different level-1 groups of the same level-2 group having different energy efficiency characteristics, and each level-2 group configured to be assigned tasks by a respective level-2 scheduler; and a level-3 group including the one or more level-2 groups and configured to be assigned tasks by a level-3 scheduler.
Abstract:
Methods and apparatus are provided for adaptive optimization of low-power strategies. In one novel aspect, the device monitors one or more thermal-performance parameters and determines a plurality of operation scenarios for a plurality of corresponding low-power policies. Based on corresponding operation scenarios, the device selects corresponding low-power policy. The device applies different low-power strategy for temperature control based on low-power policies. Different low-power policy is applied to different low-power techniques, such as the DVFS, the CPU hot-plug, and the task migration. In another novel aspect, the device obtains one or more user-defined policy for each corresponding low-power technique. The selection of each low-power policy is further based on its corresponding user-defined policy. In one embodiment, the user-defined DVFS policy includes power policy, performance policy, and DVFS-balanced policy. The user-defined CPU hot-plug policy includes conservative policy, aggressive policy, and hot-plug-balanced policy. The user-defined task-migration policy includes performance policy, and task-migration-balanced policy.
Abstract:
A multicore processor system utilizes a power manager for improving power consumption. The system includes multiple processing units and multiple power sources. Each power source is connected to two or more processing units. A condition for activating a processing unit is detected. In response to the detected condition, the power manager identifies a power source that is connected to inactive processing units only. The power manager then activates a target processing unit among the inactive processing units connected to the identified power source.
Abstract:
A task scheduling method for a multi-core processor system includes at least the following steps: when a first task belongs to a thread group currently in the multi-core processor system, where the thread group has a plurality of tasks sharing same specific data and/or accessing same specific memory address(es), and the tasks comprise the first task and at least one second task, determining a target processor core in the multi-core processor system based at least partly on distribution of the at least one second task in at least one run queue of at least one processor core in the multi-core processor system, and dispatching the first task to a run queue of the target processor core.
Abstract:
A system performs adaptive thermal ceiling control at runtime. The system includes computing circuits and a thermal management module. When detecting a runtime condition change that affects power consumption in the system, the thermal management module determines an adjustment to the thermal ceiling of a computing circuit, and increases the thermal ceiling of the computing circuit according to the adjustment.
Abstract:
A multi-processor system performs thermal-aware task scheduling and task migration. Based on temperature measurements, the system determines one or more thermal conditions of each processor. The thermal conditions include a present temperature, a historical temperature, a predicted temperature, and thermal headroom of the processor. A scheduler identifies a target processor among the processors based on, at least in part, the one or more thermal conditions of each processor, and assigns a task to be executed by the target processor. For task migration, the system detects that a source processor satisfies a task migration criterion by comparing one or more of the thermal conditions of the source processor with corresponding thresholds. The scheduler identifies a target processor based on, at least in part, one or more of the thermal conditions of each processor, and migrates a task from the source processor to the target processor for execution.
Abstract:
Methods and apparatus are provided for adaptive optimization of low-power strategies. In one novel aspect, the device monitors one or more thermal-performance parameters and determines a plurality of operation scenarios for a plurality of corresponding low-power policies. Based on corresponding operation scenarios, the device selects corresponding low-power policy. The device applies different low-power strategy for temperature control based on low-power policies. Different low-power policy is applied to different low-power techniques, such as the DVFS, the CPU hot-plug, and the task migration. In another novel aspect, the device obtains one or more user-defined policy for each corresponding low-power technique. The selection of each low-power policy is further based on its corresponding user-defined policy. In one embodiment, the user-defined DVFS policy includes power policy, performance policy, and DVFS-balanced policy. The user-defined CPU hot-plug policy includes conservative policy, aggressive policy, and hot-plug-balanced policy. The user-defined task-migration policy includes performance policy, and task-migration-balanced policy.