FPGA Hardware Accelerated Pattern Indexing
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Solution Overview
Problem
Conventional indexing techniques are computationally intensive and time-consuming, making it impractical for enterprises to index large volumes of unstructured data, which constitutes the bulk of their data, leading to inefficient data management and search capabilities.
Innovation Solution
Hardware-accelerated metadata generation using a coprocessor, such as a reconfigurable logic device, to stream data and generate metadata at bus bandwidth rates, enabling the creation of rich indexes for efficient data searching and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional indexing techniques are used, then data can be indexed with basic processing capabilities, but indexing latency is high and processing speed is slow
Solution Approach 1:
The patent replaces conventional software-based indexing mechanisms with hardware-accelerated processing using FPGAs and coprocessors. This substitution of mechanical/software systems with dedicated hardware circuits enables parallel processing of data streams, achieving bus bandwidth rates for metadata generation and dramatically reducing indexing latency while increasing processing speed.
Solution Approach 2:
The patent introduces intermediate processing layers including FPGA-based coprocessors and metadata generation hardware that act as mediators between data sources and the main processing system. These intermediaries perform preliminary metadata extraction and indexing operations, offloading work from the main processor and enabling high-speed parallel processing without bottlenecking the overall system.
2Productivity
If hardware acceleration is implemented, then indexing speed increases and latency reduces, but device complexity increases
Solution Approach 1:
The patent segments the indexing system into distinct functional modules: data ingestion interfaces, FPGA-based coprocessors for metadata generation, hardware pattern matchers, and result aggregation components. Each segment handles specific processing tasks independently, enabling parallel operation and high throughput while maintaining manageable complexity through modular design and clear interface definitions.
Data Source
AI summary
Disclosed herein is a method and system for accelerating the generation of pattern indexes. In exemplary embodiments, regular expression pattern matching can be performed at high speeds on data to determine whether a pattern is present in the data. Pattern indexes can then be built based on the results of such regular expression pattern matching. Reconfigurable logic such a field programmable gate arrays (FPGAs) can be used to hardware accelerate these operations.


