FPGA Trading Architecture for Deterministic Parallel Matching
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Solution Overview
Problem
Current electronic trading systems face challenges in maintaining transactional determinism, fault tolerance, low latency processing, high volume capacity, risk mitigation, and equitable access to information and opportunities under increasing transaction loads, particularly with the rise of high-frequency trading and global business demands.
Innovation Solution
Implementing an FPGA-based trading system architecture with redundant match engines, an Orderer component for transaction sequencing, and a Decider component for result determination, along with a market monitoring system, to ensure deterministic and fault-tolerant operation while improving transaction processing performance and market protections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional electronic trading systems are used, then basic trading functions are provided, but transactional determinism and fault tolerance deteriorate under increasing transaction loads
Solution Approach 1:
The trading system is divided into multiple independent match engines that process transactions in parallel. Each match engine handles a subset of transactions independently, allowing the system to scale processing capacity while maintaining deterministic behavior within each engine. This segmentation resolves the contradiction by enabling high throughput through parallelism while preserving transactional determinism at the individual engine level.
Solution Approach 2:
An Orderer component is introduced as an intermediary that sequences incoming transactions before distributing them to match engines. This mediator ensures that transactions are processed in a deterministic order across the distributed system, maintaining transactional determinism while enabling parallel processing through multiple engines. The Orderer acts as the coordinating intermediary that reconciles parallel processing with deterministic outcomes.
2Reliability
If redundant match engines are implemented, then fault tolerance is improved, but system complexity increases
Solution Approach 1:
The system uses multiple independent match engines that are simple, standardized components. Each engine is a self-contained unit with identical functionality, making them easy to replicate and manage. This segmentation into simple, identical units provides fault tolerance through redundancy while keeping individual components simple, resolving the complexity issue.
Solution Approach 2:
Instead of creating complex, customized redundant systems, the patent uses simple copies of the same match engine design. Each match engine is an identical copy that can independently process transactions. This copying approach provides fault tolerance through redundancy while avoiding the complexity of designing and managing heterogeneous redundant systems.
3Productivity
If high-speed processing is implemented, then transaction throughput is improved, but latency variability increases affecting determinism
Solution Approach 1:
The Orderer component performs preliminary sequencing of transactions before they enter the parallel processing stage. By pre-ordering transactions and assigning them to specific match engines in advance, the system eliminates runtime decision-making that would cause latency variability. This preliminary action ensures deterministic processing order while maintaining high throughput through parallel execution.
Solution Approach 2:
The patent replaces traditional centralized sequential processing mechanics with a distributed parallel processing system coordinated by the Orderer. This substitution allows multiple transactions to be processed simultaneously without the sequential bottlenecks that cause latency variability, while the Orderer's pre-established sequencing maintains determinism.
4Reliability
If centralized clearing is used, then credit risk mitigation is achieved, but processing efficiency decreases under high volume
Solution Approach 1:
The clearing function is segmented across multiple match engines that operate in parallel, each handling a portion of the transaction volume. This segmentation distributes the processing load while maintaining the centralized clearing model's risk mitigation capabilities, as all engines follow the same clearing rules and protocols. The segmentation resolves the efficiency problem without sacrificing credit risk mitigation.
Data Source
AI summary
The disclosed embodiments relate to implementation of a trading system, which may also be referred to as a trading system architecture, having improved performance which further assures transactional determinism under increasing processing transaction loads while providing improved trading opportunities, fault tolerance, low latency processing, high volume capacity, risk mitigation and market protections with minimal impact, as well as improved and equitable access to information and opportunities.