Dynamic power consumption control method for multithread predication by stack depth

Abstract

A dynamic power consumption controlling method using the depth of stacking for multithreading prediction is suitable for supplying power to the battery. The method includes various idle mode components of low power consumption and uses the devices of multi-task imbedded system. The method includes the following steps: step one: using the cluster mode of operating request to describe the characteristics of the sequence Phi of operating request by a single thread to the components and devices; step 2: using two-stage hashtable to predict the probability distribution of the request interval under single thread mode; step 3, taking the thread as an independent request source and grouping the request source according to the task to which the thread belong and the entry address of the thread; step 4: calculating, according to the possibility distribution of the idle time of the components or devices, the optimum overtime threshold kopt and the optimum power consumption mode sopt under multiple power consumption modes and single thread. The method improves the effective hit rate for prediction and further reduces the power consumption for the idle consumption-manageable components.

Description

technical field [0001] The invention is applicable to devices powered by batteries, having multiple idle low power consumption mode components, and adopting multi-task embedded systems. The invention belongs to the technical field of embedded system low power consumption. Background technique [0002] Many components of an embedded system are capable of operating in a variety of power and performance levels, allowing for reduced power consumption at a performance cost. For example, the processor provides various operating frequencies and operating voltages, and the hard disk provides various idle low power consumption modes such as idle, standby, and sleep. Since switching between modes generally has a performance and power consumption penalty, it is not the case that the lower the power consumption of entering idle mode for any length of idle time, the better. The optimal low power consumption mode that can be entered during different lengths of idle time will be differen...

AI Technical Summary

Problems solved by technology

The single request source model of the traditional dynamic power management strategy will make it difficult to analyze the non-stationary load, and the strategy prediction effect is not ideal

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