Multi-Market Order Book Consolidation With FPGA Parallel Processing
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Solution Overview
Problem
Current multi-market order book consolidation systems suffer from high latency and lack flexibility, making them unsuitable for high-frequency trading, particularly due to their reliance on software-implemented general purpose processors and sequential data processing, which introduces significant delays during data bursts and fails to provide participant-specific consolidated feeds with low enough latency.
Innovation Solution
The use of integrated circuits, including FPGAs and ASICs, configured to receive and consolidate market data in parallel, reducing latency to less than five microseconds by employing digital logic gates and comparator circuits that process market data in parallel, allowing for real-time calculation of round-lot quantities and participant-specific feeds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software-implemented general purpose processors are used for market data consolidation, then flexibility and adaptability are improved, but latency increases significantly
Solution Approach 1:
The system segments market data consolidation into multiple parallel processing pipelines, each handling specific data streams or instruments. This allows simultaneous processing of multiple data feeds without sequential bottlenecks, reducing overall latency while maintaining flexibility through configurable pipeline assignments.
Solution Approach 2:
The patent replaces software-based general purpose processor implementations with hardware-based Field Programmable Gate Array (FPGA) implementations. This substitution transitions from sequential software execution to parallel hardware logic operations, achieving nanosecond-scale latency reduction while preserving reconfigurability through FPGA programmability.
2Device complexity
If sequential data processing is used, then system complexity is reduced, but productivity and data burst handling capability deteriorate
Solution Approach 1:
The consolidation system is divided into multiple independent processing stages and parallel data paths that operate simultaneously. Each stage handles specific aspects of data consolidation (e.g., data reception, normalization, aggregation, output), allowing high-throughput processing during data bursts while keeping individual stage complexity manageable.
Solution Approach 2:
Multiple market data feeds from different sources are merged and consolidated into a unified order book structure through parallel processing. The system combines data from multiple exchanges and venues simultaneously, aggregating liquidity and price information across all sources in real-time without sequential bottlenecks.
3Device complexity
If standard processing latency is accepted, then system simplicity is maintained, but reliability for high-frequency trading deteriorates
Solution Approach 1:
The system replaces software-based processing with hardware-based FPGA implementations that execute consolidation logic in parallel logic circuits. This achieves deterministic nanosecond-scale latency with predictable timing characteristics, ensuring reliable and accurate price discovery for high-frequency trading without introducing software jitter or variability.
Solution Approach 2:
The system pre-configures processing pipelines and data paths in advance through FPGA programming, establishing optimized data flow routes before trading begins. This preliminary configuration ensures that during live trading, data flows through pre-validated paths with guaranteed timing, eliminating runtime decision-making delays and ensuring reliable performance.
Data Source
AI summary
The present disclosure provides techniques and associated systems for low-latency integrated circuit-based feed handler circuits and multi-market order book consolidator circuits. In some embodiments, integrated circuit-based feed handler circuits described herein can be configured to store aggregate quantities of instruments and/or determine round-lot price levels in a parallel hardware configuration. In some embodiments, integrated circuit-based order book consolidator circuits described herein can be configured to determine consolidated prices across multiple market data feeds and/or for different groups of markets in parallel hardware configurations. According to various embodiments, aspects of the present disclosure can be implemented using one or more FPGAs, ASICs, and/or combinations thereof.