Fetch Circuitry Prediction Adjustment for Instruction Execution Regions
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Solution Overview
Problem
Existing data processing systems face performance issues due to incorrect instruction predictions, which lead to wasted resources and energy, as they either fail to fetch required instructions in time or fetch unnecessary ones, occupying storage space.
Innovation Solution
The system employs a fetch circuitry with prediction components that anticipate instruction requirements, utilizing prediction tracking circuitry to maintain performance metrics for each execution region, allowing for dynamic adjustment of prediction actions based on accuracy, such as inhibiting poorly performing components to reduce incorrect predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If prediction components fetch instructions in advance, then system performance is improved, but incorrect predictions cause resource waste and energy consumption
Solution Approach 1:
The patent implements feedback mechanisms where prediction performance metrics are monitored and fed back to adjust prediction behavior. The system tracks prediction accuracy and uses this feedback to dynamically modify prediction actions, thereby reducing energy waste from incorrect predictions while maintaining performance benefits from accurate ones.
Solution Approach 2:
The patent introduces dynamic adjustment of prediction components based on performance metrics. Prediction behavior is not static but adapts in real-time based on observed performance, allowing the system to optimize the balance between fetching instructions in advance (for performance) and avoiding incorrect predictions (to reduce energy waste).
2Productivity
If prediction components fetch instructions in advance, then system performance is improved, but incorrect predictions occupy storage space in cache
Solution Approach 1:
The system monitors prediction accuracy and uses this feedback to adjust prediction behavior. When prediction performance degrades, the system reduces aggressive prediction actions, thereby freeing cache storage space while maintaining adequate instruction supply for performance.
Solution Approach 2:
The patent changes prediction parameters dynamically based on performance metrics. By adjusting prediction parameters such as prediction distance or prediction aggressiveness, the system optimizes the balance between having instructions ready in cache (for performance) and avoiding cache pollution from incorrect predictions.
3Measurement precision
If multiple prediction components are used, then prediction accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the prediction function into multiple specialized prediction components, each handling different aspects of prediction. This segmentation allows for improved overall prediction accuracy through division of labor while organizing complexity into manageable, modular units that can be independently tracked and adjusted.
Solution Approach 2:
The patent implements a universal prediction tracking and adjustment mechanism that manages multiple prediction components. This multi-functional system provides a unified approach to monitoring and adjusting various prediction components, reducing the overhead complexity that would otherwise arise from managing each component separately.
Data Source
AI summary
An example apparatus comprises instruction execution circuitry and fetch circuitry to fetch, from memory, instructions for execution by the instruction execution circuitry. The fetch circuitry comprises a plurality of prediction components, each prediction component being configured to predict instructions in anticipation of the predicted instructions being required for execution by the instruction execution circuitry. The fetch circuitry is configured to fetch instructions in dependence on the predicting. The apparatus further comprises prediction tracking circuitry to maintain, for each of a plurality of execution regions, a prediction performance metric for each prediction component. The fetch circuitry is configured, based on at least one of the prediction performance metrics for a given execution region, to implement a prediction adjustment action in respect of at least one of the prediction components.