Extended Memory Training for Overclocked Settings
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Solution Overview
Problem
Conventional memory training systems are constrained by limited boot time, preventing optimal performance with desired settings due to insufficient training time, particularly for overclocked settings.
Innovation Solution
Extended training mode is introduced, allowing for a longer duration of memory training operations during the boot-up phase, enabling more thorough configuration of memory settings, including overclocked settings, to improve signal integrity and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional memory training is performed during boot-up, then the system can start quickly, but the memory cannot achieve optimal performance with desired settings
Solution Approach 1:
The patent implements dynamic training mode selection that adapts between extended training mode (for optimal performance) and fast training mode (for quick boot-up). The system dynamically chooses the appropriate training duration and operations based on system state, allowing flexibility to prioritize either performance or speed as needed.
Solution Approach 2:
The patent changes training parameters including duration, operation types, and intensity levels. Extended training performs additional training operations and uses different timing parameters compared to fast training, allowing the system to optimize memory performance when time permits while maintaining quick startup when needed.
2Manufacturing precision
If extended training operations are performed, then signal integrity and stability improve, but the training time increases
Solution Approach 1:
The patent applies partial action by performing a subset of training operations appropriate to the selected mode. Fast training performs essential training operations with reduced duration and fewer iterations, while extended training performs complete training operations with full duration and multiple iterations, achieving optimal signal integrity when needed.
Solution Approach 2:
The training process is segmented into different phases and operation types. The patent divides training into initialization phase, calibration phase, and validation phase, allowing selective execution of phases based on the chosen training mode, thus balancing thoroughness with time constraints.
Data Source
AI summary
Extended training for memory is described. In accordance with the described techniques, a training request to train a memory with extended training is received. The extended training corresponds to a longer amount of time than a default training. The extended training of the memory is performed using a set of target memory settings. In one or more implementations, the extended training is performed during a boot up phase of the computing device.