Memory Controller Read Training Phase Interpolator Alignment
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Solution Overview
Problem
Existing memory systems face challenges in accurately aligning data sampling signals with the data eye during read operations, leading to potential bit errors and inefficiencies in data transmission between memory controllers and modules.
Innovation Solution
The implementation of a three-phase training process involving fine read training, coarse read training, and advanced read training, utilizing a side band signal lane for the memory module to adjust the phase interpolator, allowing the memory controller to determine optimal read offset timing and improve data sampling alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a phase interpolator is used to align data sampling signals, then data sampling alignment is improved, but device complexity increases due to the need for training processes and control logic
Solution Approach 1:
The patent applies preliminary action by performing read training operations before normal read operations to pre-align the phase interpolator. The training process establishes optimal phase alignment in advance, so that during normal operation the phase interpolator is already configured correctly, eliminating the need for continuous complex control logic.
Solution Approach 2:
The system applies self-service by using the memory module itself to generate training data patterns and return them for analysis. The memory module serves its own alignment calibration needs by providing test data that the controller can use to automatically adjust the phase interpolator without external intervention or complex external testing equipment.
2Measurement precision
If multiple training phases are implemented, then measurement precision of read offset timing is improved, but loss of time increases due to extended training sequences
Solution Approach 1:
The training process is segmented into three distinct phases: fine read training for initial phase alignment, coarse read training for broader timing adjustments, and advanced read training for final optimization. This segmentation allows each phase to focus on specific aspects of alignment, making the overall process more efficient and targeted rather than using a single lengthy training sequence.
Solution Approach 2:
The training phases are implemented as periodic operations that can be executed at scheduled intervals rather than continuously. The system performs training sequences periodically during initialization or when needed, then returns to normal operation, reducing overall time loss compared to continuous training.
3Manufacturing precision
If fine read training is performed before coarse read training, then manufacturing precision of timing alignment is improved, but productivity decreases due to the inverted traditional sequence
Solution Approach 1:
The training sequence is made dynamic and adaptive rather than fixed. The system can adjust the order and depth of training phases based on actual conditions detected during operation. If fine training achieves sufficient alignment quickly, the system can skip or shorten subsequent coarse training phases, thereby maintaining precision while improving productivity.
Solution Approach 2:
The system changes operational parameters during training by adjusting phase interpolator settings, sampling timing, and data rate based on measurements taken during each training phase. These parameter changes allow the system to optimize alignment precision while adapting the training duration to actual needs rather than always executing full training sequences.
Data Source
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AI summary
Provided are a device and computer readable storage medium for programming a memory module to initiate a training mode in which the memory module transmits continuous bit patterns on a side band lane of the bus interface; receiving the bit patterns over the bus interface; determining from the received bit patterns a transition of values in the bit pattern to determine a data eye between the determined transitions of the values; and determining a setting to control a phase interpolator to generate interpolated signals used to sample data within the determined data eye.