Hardware-software partitioning method based on greedy simulated annealing algorithm

Abstract

A hardware-software partitioning method based on a greedy simulated annealing algorithm comprises the following steps: (1) specifying the hardware-software partitioning problem as 0-1 knapsack problem, initially partitioning a task set by a greedy algorithm with low time complexity, and setting the partitioning result as the initial value of the simulated annealing algorithm; and (2) performing the simulated annealing algorithm, which is mainly composed of two layer loops, namely an inner loop and an outer loop, wherein the inner loop can generate a new partition according to a disturbance model, and determine and accept the new partition according to an acceptance criteria; and the outer loop is used for determining whether or not to exit the loop process according to a temperature threshold and the number of new partitions which are not accepted continuously. The method provided by the invention can reduce algorithm operation time, improve search quality and reduce calculation complexity.

Description

technical field [0001] The invention mainly relates to the field of embedded system design, in particular to a method for dividing software and hardware based on a greedy simulated annealing algorithm. Background technique [0002] The division of software and hardware refers to the determination of the implementation of each module during system design to solve the mapping problem of system function modules. The partitioning of software and hardware is a key step in the co-design of embedded system software and hardware, and the result of partitioning directly determines the quality of the system design. Its basic goal is: under the condition of satisfying the design constraints, the tasks are reasonably divided into software or hardware processing units for execution, so as to achieve the optimization of system goals, specifically including the minimum hardware implementation area or the minimum running time of functional modules. According to different target architectur...

AI Technical Summary

Problems solved by technology

These algorithms have achieved certain results in their respective fields, but most of the existing methods combine two heuristic algorithms for hardware and software division, and it is difficult to avoid problems such as the difficulty in determining the initialization parameters of the heuristic algorithm and the long initial training process.

Improper handling of these issues can lead to excessively long running times of the algorithm and reduce the probability of finding a near-optimal solution

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