Parallel Trading Signal Summarization for Low-Latency Markets
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Solution Overview
Problem
Conventional computer systems are unable to generate trading signals with sufficiently low latency and high throughput to meet the demands of Tier 1 market participants, who require immediate-term market dynamics for trading decisions.
Innovation Solution
Leveraging functional and data parallelism through integrated circuits, reconfigurable logic devices, GPUs, and multi-core processors to offload trading signal computations, enabling fine-grained parallelism and processing pipelines that generate trading signals at high speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional computer systems are used to generate trading signals, then system simplicity is maintained, but latency is too high and throughput is insufficient to meet Tier 1 market participant demands
Solution Approach 1:
The system segments trading signal generation into multiple independent processing pipelines, each handling specific computations in parallel. This segmentation enables fine-grained parallelism across multiple cores and devices, achieving the high speed required for Tier 1 market participants while managing complexity through modular architecture
Solution Approach 2:
The patent replaces conventional sequential software-based processing with hardware-accelerated parallel computing using multi-core processors, GPUs, or FPGAs. This substitution of computational mechanics enables orders of magnitude speed improvement by leveraging parallel execution capabilities of modern hardware architectures
2Productivity
If parallel processing pipelines are implemented to increase throughput, then trading signal generation speed improves, but system complexity increases
Solution Approach 1:
The processing system is divided into multiple independent pipelines that can operate in parallel, with each pipeline handling specific aspects of trading signal generation. This segmentation increases throughput while keeping individual pipeline complexity manageable
Solution Approach 2:
The parallel processing pipelines are designed to be universal and reusable across different trading strategies and market conditions. The same pipeline infrastructure serves multiple functions, increasing productivity without proportionally increasing complexity
3Loss of time
If trading signal computations are offloaded to specialized hardware, then computation speed increases by orders of magnitude, but system complexity and hardware requirements increase
Solution Approach 1:
The patent offloads trading signal computations from conventional software execution to hardware-accelerated parallel processing using multi-core processors, GPUs, or FPGAs. This substitution reduces computation time by orders of magnitude by leveraging the parallel execution capabilities of specialized hardware
Solution Approach 2:
The system uses an intermediary layer that manages the interface between conventional software and specialized hardware accelerators. This intermediary handles data transfer, task scheduling, and result aggregation, reducing computation time while managing hardware complexity through abstraction
Data Source
AI summary
Systems and methods are disclosed herein that compute trading signals with low latency and high throughput using highly parallelized compute resources such as integrated circuits, reconfigurable logic devices, graphics processor units (GPUs), multi-core general purpose processors, and/or chip multi-processors (CMPs). The trading signals can be summarized over time durations to create derived summaries of the trading signals. These derived summaries can be communicated with one or more data consumers.