Prediction Circuitry Policy Reset for Instruction Block Warm-Up
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Solution Overview
Problem
Data processing systems face performance and energy efficiency issues due to the warm-up period required for updating prediction policies when switching between different blocks of instructions, leading to reduced prediction success rates and increased energy consumption.
Innovation Solution
Incorporating a storage structure to store previous prediction policy information for blocks of instructions, allowing for immediate resetting of current prediction policies when the same block is encountered again, thereby reducing warm-up time and improving prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prediction policy information is dynamically updated based on instruction outcomes, then prediction accuracy improves over time, but a warm-up period is required which reduces initial prediction success rate and increases energy consumption
Solution Approach 1:
The patent stores previous prediction policy information in advance for blocks of instructions. When a block is encountered again, the stored prediction policy is retrieved and applied immediately, eliminating the need to go through a warm-up period. This preliminary action of storing and reusing past prediction policies resolves the contradiction by providing accurate predictions from the first instruction execution without requiring an initial learning phase.
2Measurement precision
If prediction policy information is dynamically updated based on instruction outcomes, then prediction accuracy improves over time, but energy consumption increases during the warm-up period
Solution Approach 1:
By storing prediction policy information in advance and retrieving it when blocks are reused, the system avoids the energy-consuming warm-up period. The prediction circuitry can immediately apply stored policies without performing dynamic updates and outcome tracking during initialization, thus reducing energy consumption while maintaining high prediction accuracy from the start.
3Measurement precision
If the prediction mechanism waits for warm-up before achieving accurate predictions, then prediction accuracy improves, but mode switching frequency must be reduced
Solution Approach 1:
The storage of prediction policies in advance enables immediate accurate predictions when blocks are reused, removing the constraint on mode switching frequency. The system can switch between different instruction blocks and their associated prediction modes freely without worrying about warm-up periods, thereby increasing productivity and mode switching frequency while maintaining high prediction accuracy.
Data Source
AI summary
An apparatus comprises prediction circuitry (40, 100, 80) for determining, based on current prediction policy information (43, 82, 104), a predicted behavior to be used for processing instructions. The current prediction policy information is updated based on an outcome of processing of instructions. A storage structure (50) stores at least one entry identifying previous prediction policy information (60) for a corresponding block of instructions. In response to an instruction from a block having a corresponding entry in the storage structure (50) which identifies the previous prediction policy information (60), the current prediction policy information (43, 82, 104) can be reset based on the previous prediction policy information 60 identified in the corresponding entry of the storage structure (50).