Programmable DRAM Training Sequences for Faster Interface Calibration
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Solution Overview
Problem
Modern DRAM technologies and diverse computing environments require flexible, robust, and efficient training algorithms for memory interface calibration due to variations in manufacturing and computing environments, with constraints on training time and user expectations for immediate device initialization.
Innovation Solution
A programmable sequencer orchestrates DRAM command sequences, interleaved with CSR and MISC commands, to calibrate operational parameters of internal and external datapaths through iterative adjustments based on data exchange, using a training engine with components like a sequencer, pattern generator, and correlator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If thorough training is performed to compensate for manufacturing variations and ensure high performance, then reliability is improved, but training time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing optimal training sequences in a lookup table during manufacturing. This allows the training process to quickly retrieve pre-computed sequences rather than performing exhaustive searches during initialization, thereby maintaining high reliability while significantly reducing training time.
Solution Approach 2:
The patent implements dynamics by adapting the training sequence selection based on real-time feedback from correlation measurements. The system dynamically adjusts which pre-computed sequences to test and in what order, optimizing the training process for each specific hardware instance while maintaining reliability through iterative refinement.
2Manufacturing precision
If a large searching space for voltage offsets and timing delays is explored to ensure accurate calibration, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent reduces device complexity by pre-computing optimal training sequences during manufacturing and storing them in lookup tables. This eliminates the need for complex real-time optimization algorithms, while still enabling thorough exploration of the voltage offset and timing delay parameter space to achieve high calibration precision.
Solution Approach 2:
The patent applies parameter changes by systematically varying voltage offsets and timing delays according to pre-determined sequences from the lookup table. This approach enables comprehensive exploration of the parameter space for accurate calibration while using simple, deterministic sequence generation rather than complex adaptive algorithms.
3Adaptability or versatility
If periodic calibration is performed to adapt to changing computing environments, then adaptability is improved, but productivity decreases
Solution Approach 1:
The patent enables rapid periodic calibration by using pre-computed training sequences stored in lookup tables. When environmental changes detected, the system can quickly retrieve and execute appropriate training sequences without performing exhaustive searches, thus maintaining adaptability while minimizing the time lost to re-calibration.
Solution Approach 2:
The patent implements periodic calibration at optimized intervals based on environmental change detection. Rather than continuous calibration, the system performs training periodically when needed, using the fast lookup table approach to ensure each calibration cycle completes quickly, thereby maintaining adaptability while preserving productivity.
Data Source
AI summary
Methods and systems are disclosed for training, by a sequencer of a memory interface system, an interface with DRAM. Techniques disclosed comprise scheduling a command sequence, including DRAM commands that are interleaved with one or more CSR commands; executing the scheduled command sequence, wherein the DRAM commands are sent to the DRAM through an internal datapath of the system and the CSR commands are sent to the internal datapath; and training the interface based on exchange of data, carried out by the DRAM commands, including adjustments to an operational parameter associated with the interface.