Fine-Granularity Deserializer With Defective-Lane Compensation
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Solution Overview
Problem
High-speed serializer/deserializer (SerDes) systems face challenges in maintaining low latency and strong reliability, availability, and serviceability (RAS) characteristics due to frequency and phase differences between sender and receiver clocks, as well as defective transmission lanes, leading to latency penalties and performance degradation.
Innovation Solution
The implementation of a computer-implemented method and system that uses fine-granularity deserialization techniques and defective-lane data restructuring to dynamically adjust synchronization modes and reroute data, enabling continued operation even when synchronous data transmission is disrupted, with automated diagnosis and compensation for defective lanes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous data transmission is used, then data integrity is maintained, but latency increases and reliability decreases when frequency/phase differences occur
Solution Approach 1:
The system dynamically transitions between synchronous and asynchronous operation modes based on detected lane quality and frequency/phase alignment. When lanes are defective or frequency differences are detected, the system switches to asynchronous mode with adjusted deserialization ratios, allowing continuous operation without strict timing constraints while maintaining data integrity through reorganization logic.
Solution Approach 2:
The system changes operational parameters including deserialization ratio and synchronization mode based on detected conditions. When frequency or phase differences are detected, the deserialization ratio is adjusted (e.g., from 1:1 to other ratios) and the system transitions from synchronous to asynchronous operation, optimizing performance for the current transmission conditions.
2Loss of time
If fine-granularity deserialization is implemented, then latency is reduced, but system complexity increases
Solution Approach 1:
The deserialization process is divided into fine-granularity stages with multiple deserializers operating in parallel at different granularities. Data is processed through multiple FIFO buffers and reorganization logic, allowing latency reduction through pipelining while managing complexity through modular architecture.
Solution Approach 2:
The system adds temporal dimension to deserialization by implementing multi-stage pipelines with different timing characteristics. Data flows through multiple processing stages with adjustable buffering, transforming a single complex deserialization operation into multiple simpler staged operations that can be optimized independently.
3Reliability
If defective lane compensation is implemented, then availability is improved, but device complexity increases
Solution Approach 1:
The system continuously monitors transmission lane quality through feedback mechanisms, detecting defective lanes and frequency/phase alignment status. This feedback drives automatic adjustment of deserialization parameters and switching between synchronous/asynchronous modes, improving availability without requiring manual intervention while managing complexity through automated control.
Solution Approach 2:
The system performs self-diagnosis and self-correction by automatically detecting defective lanes and adjusting operation accordingly. The deserialization logic autonomously reorganizes data paths and switches modes based on detected conditions, providing self-service error recovery that improves availability without external intervention.
4Loss of time
If asynchronous operation mode is used, then latency is reduced and robustness to frequency differences is improved, but data synchronization difficulty increases
Solution Approach 1:
The system performs preliminary organization of deserialized data into structured formats with metadata and timing information before final processing. FIFO buffers are pre-configured with specific depths and timing characteristics, and reorganization logic is prepared in advance to handle various asynchronous arrival patterns, reducing latency while managing synchronization complexity through pre-planned data structures.
Data Source
AI summary
Embodiments of the invention are directed to a computer-implemented method of operating a data transmission system. The data transmission system includes a transmitter and a receiver. The computer-implemented method includes using the transmitter to send serialized data from the transmitter through a plurality of lanes to the receiver. The transmitter sends the serialized data at a first serialization ratio. The receiver is configured to receive and load the serialized data at a second deserialization ratio, wherein the first serialization ration is greater than the second deserialization ratio.