Prediction Circuitry for Fetching Process Iteration Count
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Solution Overview
Problem
Existing data processing systems face challenges in predicting the number of iterations of a fetching process, leading to inefficient data fetching and processing operations.
Innovation Solution
The system incorporates prediction circuitry that uses prediction state information to predict the number of iterations of a fetching process, allowing for tolerance of unnecessary iterations and adjusting prediction state based on actual iteration counts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system performs iterative fetching process with predicted number of iterations, then data fetching can be performed earlier improving productivity, but performance degradation occurs due to mispredictions and unnecessary iterations
Solution Approach 1:
The system performs preliminary prediction of the number of iterations before actually executing the iterative fetching process. The prediction circuitry uses prediction state information to forecast how many iterations will be needed, allowing data fetching to start earlier than waiting for actual iteration resolution, thereby improving productivity while managing energy loss through accurate prediction
Solution Approach 2:
The system implements feedback mechanisms where the actual number of iterations is monitored and used to update the prediction state information. When mispredictions occur or unnecessary iterations are detected, the prediction circuitry adjusts future predictions based on this feedback, reducing performance degradation from repeated mispredictions while maintaining early data fetching benefits
2Loss of energy
If the system increases prediction accuracy to reduce unnecessary iterations, then energy efficiency improves, but prediction training complexity increases
Solution Approach 1:
The system accepts a range of prediction values rather than requiring exact accuracy. By tolerating some over-prediction (performing slightly more iterations than minimum needed), the system achieves sufficient energy efficiency without implementing complex prediction training schemes, as the prediction circuitry only needs to distinguish between adequate and inadequate predictions rather than achieving precise iteration counts
Solution Approach 2:
The prediction circuitry automatically adjusts its own prediction state information based on observed actual iteration counts and misprediction patterns. This self-training mechanism reduces the need for external complex training procedures while improving energy efficiency through progressively more accurate predictions that adapt to actual workload patterns
3Device complexity
If the system tolerates over-prediction to simplify prediction logic, then device complexity reduces, but productivity decreases due to unnecessary iterations
Solution Approach 1:
The system changes the prediction parameter from exact iteration count to a threshold-based adequacy metric. The prediction circuitry determines whether a predicted number is 'adequate' rather than calculating precise iteration counts, simplifying prediction logic while limiting productivity loss by ensuring predictions meet minimum adequacy thresholds for efficient processing
4Reliability
If the system performs more iterations to ensure complete data fetching, then reliability of data processing improves, but loss of time increases due to unnecessary iterations
Solution Approach 1:
The system performs preliminary prediction of adequate iteration counts before execution. By forecasting the sufficient number of iterations needed for complete data fetching, the system ensures processing reliability while avoiding the time loss associated with extensive trial-and-error or excessive iterations, as the prediction guides the fetching process from the start
Data Source
AI summary
Prediction circuitry predicts a number of iterations of a fetching process to be performed to control fetching of data/instructions for processing operations that are predicted to be performed by processing circuitry. The processing circuitry can tolerate performing unnecessary iterations of the fetching process following an over-prediction of the number of iterations. In response to the processing circuitry resolving an actual number of iterations, the prediction circuitry adjusts the prediction state information used to predict the number of iterations, based on whether a first predicted number of iterations, predicted based on a first iteration prediction parameter, provides a good prediction (when the first predicted number of iterations is in a range i_cnt to i_cnt+N, where i_cnt is the actual number of iterations and N≥1), or a misprediction (when the first predicted number of iterations is outside the range i_cnt to i_cnt+N).