Barrel Compactor Data Extraction Without Wide Multiplexors
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Solution Overview
Problem
Existing data processing devices are expensive due to the use of large multiplexors for data extraction, which are costly and inefficient for handling large quantities of input data.
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 high-cost 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 smaller multiplexors that operate in parallel stages. Instead of using one large multiplexer to handle all input data simultaneously, the system segments the extraction process into multiple passes, where each pass uses smaller, more cost-effective multiplexors to extract specific subsets of data from different portions of the input dataset.
Solution Approach 2:
The invention adds a temporal dimension to the data extraction process by performing extraction in multiple sequential passes rather than a single simultaneous operation. This allows the system to extract different data subsets across multiple time cycles, effectively replacing a large spatial structure (one big multiplexer) with a combination of smaller structures operating over time.
2Productivity
If large multiplexors are used for data extraction, then data extraction capability is improved, but device complexity increases
Solution Approach 1:
The complex function of a large multiplexer is segmented into multiple simpler multiplexing stages. Each stage handles a portion of the data with a smaller multiplexer, reducing the complexity of individual components while maintaining overall extraction capability through coordinated operation of multiple stages.
Solution Approach 2:
The system performs preliminary data organization and preliminary extraction passes before final data collection. By preparing and partially processing data in advance through multiple passes, the system reduces the complexity of the final extraction operation and distributes the computational burden across multiple simpler steps.
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.