Barrel Compactor Architecture Using Staged Multiplexors for Packet Extraction
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Solution Overview
Problem
Existing data processing devices that use large multiplexors for data extraction are expensive due to the high cost of these devices, which limits the efficiency and cost-effectiveness of data extraction processes.
Innovation Solution
A barrel compactor system that selectively shifts data units within an input dataset based on individual shift values, allowing for the extraction of a desired subset by rearranging data units to be adjacent to each other, thereby eliminating the need for expensive wide multiplexors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large multiplexors are used for data extraction, then data extraction capability is improved, but device cost increases
Solution Approach 1:
The invention divides the data extraction function into multiple stages using a series of smaller multiplexors instead of one large multiplexor. Each multiplexor in the sequence handles a portion of the data units, progressively filtering and extracting the desired subset. This segmentation allows the system to achieve the same extraction capability as a large multiplexor while using multiple smaller, less expensive components.
Solution Approach 2:
The invention transforms the data extraction process from a single-dimension operation (one large multiplexor selecting from all input data units) into a multi-dimensional process using an array of multiplexors arranged in rows and columns. Data units are processed through multiple passes, with each pass performing a portion of the extraction task. This dimensional transformation enables cost-effective extraction by distributing the workload across multiple smaller devices.
2Ease of manufacture
If a series of multiplexors are used instead of a large multiplexor, then device cost is reduced, but device complexity increases
Solution Approach 1:
The invention designs each multiplexor in the array to perform multiple functions: data selection, data passing, and control signal generation. Each multiplexor can operate in different modes depending on the extraction requirements, serving as both a filtering element and a routing element. This multi-functionality reduces the need for specialized components, simplifying the overall system architecture despite using multiple multiplexors.
Solution Approach 2:
The invention implements a nested structure where multiplexors are arranged in an array with rows and columns, and each multiplexor processes data that has been partially filtered by previous multiplexors in the sequence. The output of one multiplexor becomes the input for the next, creating a nested processing hierarchy. This nesting allows the system to manage complexity by organizing multiple components in a structured, hierarchical manner rather than as a flat collection of independent elements.
Data Source
AI summary
A packet processing system having a barrel compactor that extracts a desired data subset from an input dataset (e.g. an incoming packet). The barrel compactor is able to selectively shift one or more of the input data units of the input dataset based on individual shift values for those data units. Additionally, in some embodiments one or more of the data units are able to be logically combined to produce a desired logical output unit.