Parallel Framing State Machines for GFP Frame Location
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Solution Overview
Problem
Existing methods for locating GFP frames encapsulated within a clock cycle are inefficient due to the short duration of the clock cycle, leading to failure in identifying the correct starting byte of the GFP frame when multiple frames are encapsulated, resulting in incorrect frame location.
Innovation Solution
A method where a framing state machine is allocated to each byte of the data stream within a clock cycle, allowing concurrent hunting for data frames from respective corresponding bytes, with the results from previous cycles used to determine and match the starting byte of the first data frame within the current cycle, ensuring accurate frame location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single framing state machine performs byte-by-byte hunting in the HUNT state, then the method is simple to implement, but the frame location accuracy deteriorates when multiple frames are encapsulated within a clock cycle
Solution Approach 1:
The patent divides the single framing state machine into multiple parallel framing state machines, with each state machine responsible for hunting frames starting from a specific byte position. This segmentation allows simultaneous multi-position hunting within the same clock cycle, resolving the contradiction by maintaining simple individual state machine structures while achieving accurate multi-frame location through parallel execution.
2Productivity
If the hunt period is extended to cover the entire clock cycle, then more frames can be located, but the time required for frame location increases
Solution Approach 1:
The patent pre-calculates and stores the starting byte positions of frames from previous clock cycles in a lookup table. During the current clock cycle, the system uses this pre-stored information to quickly determine where to start hunting and how long the hunt period should be, eliminating the need to scan the entire previous cycle and significantly reducing current cycle time while maintaining high productivity.
Solution Approach 2:
The patent introduces a time dimension by utilizing information from previous clock cycles to inform the current cycle's frame location process. By storing and referencing historical frame position data, the system extends its effective search capability without increasing the current cycle's processing time, thereby improving productivity without sacrificing time efficiency.
3Speed
If multiple framing state machines perform concurrent hunting from different bytes, then frame location speed increases, but the device complexity increases
Solution Approach 1:
The patent implements multiple framing state machines that share common resources including the same state transition logic, lookup table structure, and control signals. Each state machine is a universal template instantiated at different positions, allowing them to function independently yet cooperatively. This multi-functionality approach increases frame location speed through parallelism while minimizing the actual increase in device complexity by avoiding duplication of shared components.
Data Source
AI summary
The present invention provides a method for locating a data frame. The method mainly includes: allocating a framing state machine to each byte of a data stream within a current clock cycle; respectively starting, by the framing state machines, hunting for data frames from respective corresponding bytes, and obtaining a plurality of data frame hunt results; and selecting one hunt result from the plurality of data frame hunt results according to a data frame hunt result within a previous clock cycle as a data frame hunt result within the current clock cycle.