Branch Instruction Prediction Accuracy via Method Selection
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Solution Overview
Problem
Current branch prediction methods in processors are inaccurate, leading to significant waiting times and performance losses, as they fail to predict branch instructions effectively, resulting in processor clock cycle losses of about 20 cycles.
Innovation Solution
A method that determines a branch instruction to be predicted based on a target instruction, predicts it using multiple preset methods, evaluates the accuracy of each method, and selects the method with the highest accuracy for improved prediction, adjusting prediction states and cumulative results to enhance prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a processor uses traditional branch prediction methods, then the device complexity is low, but the branch prediction accuracy is poor causing loss of time
Solution Approach 1:
The patent segments the branch prediction task into multiple independent prediction methods (e.g., static prediction, dynamic prediction, pattern-based prediction). Each method operates independently and contributes to the overall prediction decision, allowing the system to evaluate multiple approaches without increasing complexity of individual components.
Solution Approach 2:
The patent implements dynamic selection of prediction methods based on runtime conditions. The system adaptively chooses which prediction method to use based on the specific branch instruction characteristics and historical performance, making the prediction system flexible and responsive rather than static.
2Measurement precision
If a processor uses multiple branch prediction methods, then the branch prediction accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent merges multiple prediction methods into a unified prediction framework. Different prediction techniques (static, dynamic, pattern-based) are combined and evaluated together, with their results integrated to form the final branch prediction decision, maximizing accuracy while managing complexity through systematic integration.
Solution Approach 2:
The patent creates a universal prediction system that can handle different types of branch instructions using multiple prediction methods. The system is designed to be multi-functional, accommodating various prediction strategies within a single framework that adapts to different instruction patterns and scenarios.
Data Source
AI summary
The present application discloses a branch instruction processing method, system, and device, and a computer storage medium. The method includes: determining, on the basis of a target branch instruction, a branch instruction to be predicted (S101); predicting, on the basis of a plurality of preset branch prediction methods, the branch instruction to be predicted, so as to obtain a corresponding prediction result (S102); determining the prediction accuracy of each branch prediction method on the basis of the prediction result (S103); determining the branch prediction method corresponding to the highest prediction accuracy as a target branch prediction method (S104); and performing branch prediction on the target branch instruction on the basis of the target branch prediction method (S105).