Shift Register Latency Control for Sub-Nanosecond Signal Alignment
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Solution Overview
Problem
Current systems face challenges in precisely controlling processor latency, particularly in achieving intervals less than one nanosecond, with existing predictive algorithms limited to a resolution of around 3 ns.
Innovation Solution
A system and method that utilizes shift registers to sample deserialized input signals at a slow clock speed, allowing for higher granularity control of data latency between input and output signals, and employs a predictive learning algorithm to correct and control output latency within one high-speed clock cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing predictive algorithms are used to control latency, then latency control is provided, but the resolution is limited to around 3 ns
Solution Approach 1:
The patent segments the latency control function into multiple components: a coarse latency controller using shift registers for sub-nanosecond precision, and a fine latency controller using predictive algorithms for clock-period adjustments. This segmentation allows achieving higher precision (better than 3 ns) without requiring a complete redesign of the predictive algorithm system.
Solution Approach 2:
The patent introduces an intermediary mechanism between the input signal and output signal - specifically, shift registers that hold and serialize/deserialize data bits. This intermediary structure enables precise latency control by controlling the number of clock cycles data remains in the shift registers, achieving sub-nanosecond resolution without directly modifying the predictive algorithm's temporal constraints.
2Measurement precision
If shift registers sample deserialized input signal at slow clock speed, then higher granularity control of data latency is achieved, but processing speed is reduced
Solution Approach 1:
The patent employs dynamic clocking where shift registers operate at different clock speeds depending on the required latency precision. For coarse latency control, a slower clock is used to achieve higher granularity. For fine adjustments, the system dynamically switches to faster clock operations, maintaining overall processing speed while enabling precise latency control when needed.
Solution Approach 2:
The system uses periodic sampling at the slow clock speed only when precision latency adjustment is required, rather than continuously operating at slow speed. The shift registers are updated periodically at the slow clock rate for precision control, while data throughput maintains higher speeds during normal operation, thus balancing precision requirements with processing speed.
Data Source
AI summary
A system and method for serializing output includes shift registers that sample a deserialized input signal at a relatively slow clock speed. Data latency between the input and output signals is controllable to a higher granularity than the input signal with bit positions corresponding to the high-speed input signal. A predictive learning algorithm receives data latency values from the input signal and corresponding data latency values from the output signal to correct and control output latency, potentially within one high speed clock cycle.