Hardware-Accelerated Delimited Data Translation Pipeline
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Solution Overview
Problem
Delimited data formats, such as CSV, pose challenges in processing due to the serial nature of byte-by-byte delimiter and shield character detection, leading to bottlenecks in throughput as general-purpose processors struggle to efficiently validate and process data fields like zip codes without analyzing all preceding bytes.
Innovation Solution
The implementation of a data translation pipeline that converts delimited data into structured formats like fixed field or mapped variable field formats, utilizing reconfigurable logic and modular processing to enable direct access to specific fields, thereby bypassing the need for serial processing and improving throughput through data parallelism and hardware acceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If byte-by-byte delimiter and shield character detection is used in delimited data formats, then data processing can be performed with simple software implementations, but system throughput is limited due to the serial nature of processing
Solution Approach 1:
The patent replaces the mechanical byte-by-byte processing approach with a hardware-based parallel processing system. The hardware system uses parallel comparison logic to simultaneously analyze multiple bytes for delimiter and shield character detection, eliminating the serial processing bottleneck while maintaining the functional requirements of delimited data format parsing.
2Adaptability or versatility
If general-purpose processors are used to process delimited data, then system flexibility and adaptability are maintained, but processing speed is insufficient due to the need to analyze all preceding bytes before validating fields
Solution Approach 1:
The patent segments the data processing task into parallel operations performed by multiple hardware components. Different functional units simultaneously perform delimiter detection, shield character detection, field validation, and data transformation on different portions of the data stream, enabling both high speed and adaptability through modular hardware design.
3Quantity of substance
If serial processing of delimited data is used, then memory usage is minimized, but time consumption increases due to the need to process each byte sequentially
Solution Approach 1:
The patent transitions from one-dimensional serial processing to multi-dimensional parallel processing by implementing multiple processing pipelines that operate simultaneously on different data streams or different aspects of the same data stream. This dimensional expansion enables time reduction through parallel execution while managing memory resources efficiently through streamlined data flow architecture.
Data Source
AI summary
Various methods and apparatuses are described for performing high speed translations of data. In an example embodiment, record layout detection can be performed for data. In another example embodiment, data pivoting prior to field-specific data processing can be performed.