RTOS power optimization method based on discrete Hopfield neural network

Abstract

This invention relates to one RTOS consumption optimization method based on discrete Hopfield neural network, which comprises the following steps: by use of pattern description method to divide the RTOS consumption relative soft and hardware into one detail combination optimization problem to introduce one new module of RTOS consumption division problem; then according to the division property re-defining discrete Hopfield neural network element, energy function, operation equation parameters to use the neural network as RTOS consumption division optimization to realize the function division to reduce RTOS power consumption.

Description

Technical field [0001] The invention relates to the technical field of SoC power consumption optimization and neural network algorithms, in particular to an RTOS power consumption optimization method based on a discrete Hopfield neural network. Background technique [0002] With the continuous development of the global energy crisis, the power consumption of a large number of embedded systems has attracted people's attention day by day. As a new form of embedded system, SoC (System-on-a-Chip system or system chip) basically realizes the software / hardware functions of a complete computer system in a single IC (Integrated Chip integrated circuit chip). Compared with traditional embedded systems, SoC has many obvious advantages, such as small size, low power consumption, high reliability, and higher cost performance, etc. The disadvantages are increased complexity, high design costs, and long development cycles, which completely change the The overall design framework of the p...

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Problems solved by technology

Compared with general RTOS, because SoC-RTOS has different characteristics and application requirements, it has different function sets and software / hardware implementation requirements, resulting in the existence of RTOS-Power division and general embedded system and SoC division. There is a relatively big difference. The past software / hardware division methods are not sufficient for RTOS-Power division in many aspects, such as RTOS-Power power consumption modeling and estimation, power consumption constraints and refinement of target parameters, power consumption optimization solution Algorithm design, partition result evaluation, system structure and other issues

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