Heterogeneous multi-core processor task allocation and scheduling strategy based on genetic algorithm

Abstract

The invention provides a task allocation and scheduling strategy of a heterogeneous multi-core processor system based on a genetic algorithm. Task allocation and scheduling of the heterogeneous multi-core processor comprise task allocation in a global task scheduler and local scheduling on each processing unit, and the main process can be divided into the following steps of: converting a task in aglobal task scheduler into a directed acyclic graph according to the sequence and communication information of each subtask; wherein the directed acyclic graph is represented by a DAG graph; then sending each subtask to each processing unit, wherein each processing unit carries out processing according to a local task sequence, and finally optimizing a task allocation and scheduling scheme by using an improved genetic algorithm in the operation process, and taking an approximately optimal solution solved by the genetic algorithm as the allocation and scheduling scheme. The scheme can be directly used when the task is executed next time, the efficiency of the heterogeneous multi-core processor system is improved, and the energy consumption is reduced.

Description

technical field [0001] The invention belongs to the field of computer system structure, and specifically relates to a CPU-GPU heterogeneous multi-core processor task allocation and scheduling strategy based on genetic algorithm. Background technique [0002] With the upgrade of manufacturing process, especially the application of 7nm technology, the processor architecture has undergone tremendous changes. The traditional single-core structure is restricted by a series of reasons such as physical design limits and energy consumption, which will inevitably lead to the focus of Moore's Law being changed from The pure number of transistors is transferred to the number of cores that can be integrated on a chip. A multi-core processor integrates multiple processing units on a chip, which has obvious advantages over a single-core architecture and can run a single processor at a relatively low frequency Computing performance that requires a high frequency can improve the heat dissip...

AI Technical Summary

Problems solved by technology

[0009] Different types of processing units in a heterogeneous system have different computing capabilities. According to the characteristics of heterogeneous multi-core processors and computing tasks, the present invention proposes a CPU-GPU heterogeneous multi-core processor task allocation and scheduling strategy based on genetic algorithms. It is used to solve the problem of completing task assignment with the minimum energy consumption cost

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