Memory Link Training Signal Alignment Unit
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Solution Overview
Problem
Modern memory controllers face challenges in aligning read and write signals due to shrinking design windows and increasing variations in high volume manufacturing, leading to increased circuit complexity and limited frequency scaling with DDR technology.
Innovation Solution
A signal alignment unit within the memory controller uses a finite state machine and delayed lock loops to align read and write signals by adjusting their delays, ensuring optimal positioning and minimizing the impact of manufacturing variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If DLLs are used to center signals in the eye and recover timing margin, then signal alignment reliability is improved, but circuit area and complexity increase
Solution Approach 1:
The patent divides the signal alignment process into separate training phases (coarse training and fine training) and separates different signal types (address, command, data signals) into independent alignment operations. Each phase uses specialized DLLs configured for specific signal characteristics, reducing the complexity burden on any single component while maintaining overall reliability.
Solution Approach 2:
The patent implements preliminary coarse training before fine training, where coarse training establishes initial signal alignment using relaxed requirements, and fine training refines the alignment with stricter criteria. This preliminary action reduces the difficulty of subsequent fine-tuning operations and distributes the complexity across manageable training stages rather than requiring perfect alignment in a single complex operation.
2Measurement precision
If more training samples are used to test DLL settings, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent segments the training process into coarse training phase with fewer samples for rapid initial alignment, followed by fine training phase with more samples for precise optimization. This segmentation allows the system to achieve acceptable precision quickly through coarse training, then invest additional time only when necessary for fine-tuning, rather than uniformly collecting maximum samples throughout the entire process.
Solution Approach 2:
The patent applies partial action by using a limited number of training samples during coarse training to achieve sufficient alignment for subsequent fine training. The system collects more samples during fine training only when the coarse training indicates additional precision is needed, avoiding the excessive time consumption of collecting maximum samples from the outset while still achieving the required measurement precision.
Data Source
AI summary
An apparatus and method are disclosed. In one embodiment, the apparatus trains a memory link using a signal alignment unit. The signal alignment unit aligns a read data strobe signal that is transmitted on the link with the center of a read data eye transmitted on the link. Next, the signal alignment unit aligns a receive enable signal that is transmitted on the link with the absolute time that data returns the data lines of the link a column address strobe signal is sent to the memory coupled to the link. Next, the signal alignment unit aligns a write data strobe signal transmitted on the link with the link's clock signal. Finally, the signal alignment unit aligns the center of the write data eye transmitted on the link with the write data strobe transmitted on the link.