Smart SERDES Link Tuning for Power Reduction
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Solution Overview
Problem
Existing SERDES links consume excessive power when running at full speed and full voltage, becoming a performance limiting factor, and require inefficient multiplexing and traditional filtering methods.
Innovation Solution
The 'Smart SERDES' system reduces power consumption by individually tuning links for optimal speed and bit error rate (BER) using low-level link management, avoiding channel multiplexing, enabling peer-to-peer communications, and employing analog-artificial intelligence (AI) methods, efficient power level setting, and feed-forward control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If SERDES links run at full speed and full voltage, then data transfer performance is improved, but power consumption increases excessively
Solution Approach 1:
The patent implements dynamic voltage and speed adjustment for SERDES links based on actual communication needs. The system transitions from static full-speed operation to dynamic adaptation, adjusting operating parameters in real-time to match traffic demands, thereby reducing power consumption while maintaining required performance levels.
Solution Approach 2:
The system changes operational parameters (voltage level, link speed) of SERDES links according to actual communication requirements. By adjusting these parameters dynamically rather than operating at fixed maximum settings, the system achieves optimal balance between performance and power consumption.
2Reliability
If traditional adaptive/digital signal processing filtering is used, then signal cleaning is achieved, but device complexity and power consumption increase
Solution Approach 1:
The patent replaces complex digital signal processing filtering mechanisms with simpler analog artificial intelligence methods. This substitution reduces device complexity while maintaining signal quality through alternative physical mechanisms that achieve the same filtering objective with fewer components.
Solution Approach 2:
The system changes the approach to signal filtering by using analog AI techniques that adjust signal parameters directly in the analog domain, avoiding the need for complex digital processing chains. This reduces the number of components and overall system complexity while achieving effective signal cleaning.
3Productivity
If channel multiplexing is implemented, then resource utilization is improved, but performance degradation occurs due to interference
Solution Approach 1:
The patent segments communication channels to avoid multiplexing interference, allowing individual channel optimization. By dividing the communication architecture into separate, independently manageable channels, the system eliminates cross-channel interference while maintaining efficient resource utilization through dedicated path management.
4Device complexity
If master/servant communication architecture is used, then system control is simplified, but peer-to-peer communication efficiency is reduced
Solution Approach 1:
The patent implements dynamic communication architecture that can switch between master/servant and peer-to-peer modes based on communication requirements. This dynamic adaptation allows the system to maintain simple control when needed while achieving high efficiency through direct peer-to-peer communication when appropriate, optimizing both control simplicity and communication performance.
Data Source
AI summary
A system, method, and apparatus for serializer/deserializer (SERDES) communication. In one embodiment, power consumption is reduced by tuning links individually for best speed and/or bit error rate (BER) through use of one or more of i) low-level link management; ii) avoiding multiplexing of channels where it impacts performance, and iii) enabling peer-to-peer (p2p) communications in ostensibly master/servant scenarios. Fine tuning of link behavior is achieved with one or more techniques including i) analog-artificial intelligence (AI) methods, rather than traditional adaptive/digital signal processing (DSP) filtering; ii) efficient power level setting; and iii) feed-forward control.