Semiconductor Training System Parallel Memory Bank Optimization
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Solution Overview
Problem
Current semiconductor systems face challenges in shortening training performance time and increasing accuracy during training operations, particularly in data transmission and memory bank utilization.
Innovation Solution
A semiconductor system configuration that includes a master and slave with multiple unit memory regions, where the master writes reference and test data in these regions, and determines the center of a data eye to adjust transmission timing and voltage, optimizing training by comparing determination result data and using a pipe register for parallel data output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the master transmits data to the slave and the slave transmits data back for training operations, then the training function can check whether the slave accurately receives signals, but the training time becomes excessively long
Solution Approach 1:
The slave is divided into multiple unit memory regions (first, second, third memory regions) that can be independently accessed. The master performs training operations on different memory regions in parallel by transmitting different data patterns (first data pattern to first region, second data pattern to second region, etc.), thereby reducing total training time while maintaining comprehensive training coverage
Solution Approach 2:
The patent introduces a time dimension by overlapping training operations across multiple memory regions. Instead of sequentially training one memory region at a time, the system utilizes multiple memory regions simultaneously, effectively adding a parallel processing dimension to the training operation
2Reliability
If the system performs comprehensive training operations including command training, write training, and read training, then the training accuracy improves, but the device complexity increases
Solution Approach 1:
The slave device is designed with multi-functional memory regions that can serve different training purposes. The same unit memory regions are used for both write training (receiving data patterns) and read training (transmitting data back), as well as command training operations. This universal usage of memory regions reduces the need for dedicated hardware for each training function, thereby reducing overall system complexity
Data Source
AI summary
A semiconductor system includes a slave and a master, wherein the slave includes a plurality of unit memory regions, and is configured to transmit determination result data generated by comparing reference data and test data, to the master, and wherein the master is configured to write the reference data and the test data in the plurality of unit memory regions.