A lightweight class method for system power consumption optimization based on online learning

A system power consumption, lightweight technology, applied in design optimization/simulation, hardware monitoring, instrumentation, etc., can solve the problem of heavy system operation load, lack of robust system power consumption model, and limited ability to reduce overall system power consumption And other issues

Active Publication Date: 2017-07-28
BEIHANG UNIV
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Problems solved by technology

[0006] (1) The common system power consumption optimization is to optimize the design of low power consumption from a single level. Since the power consumption is generated by the software driver through the hardware, the low power consumption design of a single level does not take into account the influence of other levels on power consumption. Factors, so the ability to reduce the overall power consumption of the system is limited;
[0007] (2) For the method of establishing a multi-level system power consumption model, it is necessary to take into account the mutual influe...

Method used

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  • A lightweight class method for system power consumption optimization based on online learning
  • A lightweight class method for system power consumption optimization based on online learning
  • A lightweight class method for system power consumption optimization based on online learning

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Embodiment Construction

[0096] The present invention is a lightweight method for system power consumption optimization based on online learning, such as figure 1 As shown, the specific implementation steps of the method are as follows:

[0097] Step 1, generate the target code by compiling and linking the application source program code;

[0098] Step 2, using perf, the application can use the PMU and counters in the kernel to perform performance statistics and monitor hardware feature events, such as IPS, processor clock cycles, cache, and branch prediction.

[0099] Step 3: Calculate and process the system events obtained through step 2, that is, monitoring data sampled by time, using formulas (1) and (2), mainly to perform data normalization processing.

[0100] Step 4, establish a system power consumption model through formulas (3), (4) and (5), and import the data calculated in the step.

[0101] Step 5, design the first working mode adaptive optimization mode according to formulas (6), (7), (...

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Abstract

The invention provides a lightweight class method for system power consumption optimization based on online learning. The method comprises the steps of: 1, performing program compiling to generate target codes; 2, starting a monitoring module to monitor hardware events; 3, performing normalization processing of events; 4, building a system power consumption module; 5, designing different optimization modes; 6, designing a value function module; 7, writing the power consumption module, a penalty factor and the value function module into an agent module Agent; 8, designing a software timer and starting the third step and the seventh step regularly; 9, executing a program, the seventh step and the third step and updating the Agent; 10; setting convergence; 11, according to results of the Agent module, going to the second step and starting from the third step until operation is over. Through the steps, temperature, performance and power consumption are comprehensively and synergistically considered and a lightweight class machine learning algorithm is used to search for existing optimization space, so that the effects of low power consumption and reasonable performance are achieved and the problem is solved that working time is influenced because embedded devices are limited by batteries.

Description

technical field [0001] The present invention provides a lightweight method for optimizing system power consumption based on online learning, which relates to the technical field of power consumption optimization for embedded systems, and in particular to a method for combining power consumption optimization for embedded systems with machine learning algorithms. The method is applied in the power consumption optimization and power consumption estimation of the embedded system, and can improve the life cycle and performance of the embedded system. Background technique [0002] Embedded devices have been used more and more in daily life. More embedded terminals and wider online interconnection make embedded system power consumption a problem that designers must face. In addition to energy shortage and environmental protection The current situation of the processor power consumption has attracted more and more attention. Low power consumption has become an important indicator of...

Claims

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Application Information

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IPC IPC(8): G06F11/30G06F17/50
CPCG06F11/3062G06F30/20G06F2119/06Y02D10/00
Inventor 王翔李林王维克杜培李明哲
Owner BEIHANG UNIV
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