Prediction Identifier Recursion Control Using Confidence Thresholds
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Solution Overview
Problem
Existing prediction structures face a trade-off between reduced latency and cache pollution and bandwidth utilization due to recursive lookups, which can lead to high penalties when incorrect predictions are triggered.
Innovation Solution
Each prediction entry encodes prediction confidence information, allowing the prediction circuitry to suppress recursion procedures when confidence is low, thereby controlling recursive lookups and reducing unnecessary transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If recursive lookups are performed to improve prediction accuracy, then prediction reliability is improved, but cache pollution and bandwidth utilization increase
Solution Approach 1:
The patent introduces prediction confidence information as a new parameter stored with each prediction entry. This parameter allows the system to differentiate between high-confidence and low-confidence predictions, enabling selective recursion based on confidence thresholds. By changing the parameter space to include confidence levels, the system can control recursion depth and prevent unnecessary lookups that cause cache pollution.
Solution Approach 2:
The patent makes the recursion procedure dynamic by conditionally enabling it based on prediction confidence information. Instead of performing recursion uniformly for all predictions, the system dynamically adjusts its behavior - recursing only when confidence exceeds a threshold. This dynamic control allows the system to adapt recursion depth to actual prediction quality, reducing harmful cache pollution from low-confidence predictions.
2Reliability
If recursive lookups are performed to improve prediction accuracy, then prediction reliability is improved, but bandwidth utilization increases
Solution Approach 1:
The patent introduces prediction confidence information as a parameter that enables selective recursion. By storing and evaluating confidence thresholds, the system can determine whether to perform recursive lookups based on the predicted entry's confidence level. This parameter-driven approach prevents unnecessary bandwidth consumption from recursing on low-confidence predictions while maintaining reliability for high-confidence ones.
Solution Approach 2:
The patent applies partial action by performing recursion only when necessary - specifically when prediction confidence exceeds a defined threshold. Instead of uniformly recursing for all predictions (excessive action), the system selectively recurses only for high-confidence predictions, thereby reducing unnecessary bandwidth utilization while maintaining prediction reliability where it matters most.
3Ease of operation
If prediction confidence information is stored in each entry, then recursion control is improved, but device complexity increases
Solution Approach 1:
The patent makes the prediction entry structure universal by serving multiple functions: storing the prediction identifier, prediction information, and prediction confidence information all within the same entry structure. This multi-functional design allows the confidence information to be integrated into existing prediction storage hardware without requiring separate complex control structures, thereby limiting the increase in device complexity while maintaining recursion control capabilities.
Data Source
AI summary
There is provided an apparatus comprising prediction storage circuitry to store prediction entries. Each of the prediction entries is identified by a prediction identifier and comprises prediction information. The apparatus is provided with prediction circuitry responsive to receipt of a given prediction identifier to perform a lookup in the prediction storage circuitry. The prediction circuitry is configured, when the lookup results in a hit to retrieve corresponding prediction information and to trigger a transaction request. In further response to the hit, the prediction circuitry is also configured to perform a recursion procedure to determine whether the prediction information identifies further prediction identifiers, and if so, to trigger further lookups based on each of the further prediction identifiers. The prediction entries encode prediction confidence information, and the prediction circuitry is configured to suppress the recursion procedure when the prediction confidence information does not satisfy a recursive prediction condition.