Offload Processor Repackaging Financial Market Data
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Solution Overview
Problem
Current systems face challenges in minimizing latency and optimizing resource usage for processing and distributing large volumes of financial market data, particularly in electronic trading platforms, where fast access and efficient handling are critical.
Innovation Solution
The implementation of offload processors and intelligent feed switches that reconfigure and repurpose data packets, leveraging reconfigurable hardware devices to offload processing tasks from traditional platform components to network elements, thereby reducing latency and resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data processing tasks are performed by traditional platform components, then processing capability is maintained, but latency increases and resource usage is suboptimal
Solution Approach 1:
The patent extracts data processing tasks from traditional platform components and relocates them to offload processors positioned upstream in the data flow. This separation allows the main platform to focus on core trading functions while dedicated offload processors handle data filtering, repackaging, and preprocessing, thereby reducing latency without significantly increasing overall system complexity.
Solution Approach 2:
The patent introduces offload processors as intermediary components between data sources and the main trading platform. These intermediaries perform preliminary processing operations such as filtering, repackaging, and protocol conversion, reducing the processing burden on the main platform and enabling faster data delivery with minimal architectural complexity increases.
2Productivity
If more processing resources are allocated to data processing, then processing capability improves, but space and power consumption increase
Solution Approach 1:
The patent segments the data processing workload into distinct functional components distributed across multiple offload processors. Each processor handles specific tasks such as filtering, repackaging, or protocol conversion, allowing the system to achieve high throughput through parallel processing while optimizing power consumption by activating only the necessary processing segments for each data flow.
Solution Approach 2:
The patent replaces traditional mechanical processing systems with specialized offload processors that use optimized data plane processing. This substitution enables higher throughput by bypassing general-purpose CPU processing stacks and using dedicated hardware or firmware-based processing, thereby improving productivity while reducing power consumption compared to traditional software-based approaches.
3Adaptability or versatility
If data is processed and distributed through centralized platform components, then control is maintained, but scalability is limited
Solution Approach 1:
The patent moves data processing from the traditional vertical architecture (centralized platform components) to a horizontal dimension by positioning offload processors upstream in the data distribution network. This dimensional shift enables scalable deployment where multiple offload processors can be added in parallel to handle increasing data volumes without proportionally increasing the complexity of the central platform architecture.
Data Source
AI summary
Various techniques are disclosed for offloading the processing of data packets. For example, incoming data packets can be processed through an offload processor to generate a new stream of outgoing data packets that organize data from the data packets in a manner different than the incoming data packets. Furthermore, in an exemplary embodiment, the offloaded processing can be resident in an intelligent switch, such as an intelligent switch upstream or downstream from an electronic trading platform.