Low-Latency AI Trading Kernels in C++20 : GPU Acceleration, FPGA Prototyping, and Execution Strategies for Deep RL and Neural PDE Policies
Language: English
Published by Independently Published Jun 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 82.31
Quantity: 2 available
Add to basketItem description from seller
Neuware - Reactive PublishingMaster the engineering of ultra-low latency AI trading systems with this technical deep dive into modern C++20, GPU acceleration, and FPGA prototyping.This book explores the complete pipeline for building high-performance trading kernels capable of executing deep reinforcement learning (Deep RL) and neural PDE policies at extreme speeds. You will examine production-grade implementations using C++20 features, CUDA and GPU optimization techniques, and FPGA-based acceleration strategies designed for sub-microsecond decision cycles in live markets.Key topics include: - Modern C++20 architectures for low-latency kernel design- GPU acceleration patterns for neural network inference in trading- FPGA prototyping workflows for custom hardware acceleration- Integration of Deep RL agents and neural PDE solvers into real-time execution engines- Memory management, concurrency, and deterministic performance optimizationsWritten for quantitative developers, high-frequency trading engineers, and AI systems programmers, this book provides detailed code examples, architectural diagrams, and practical implementation guidance for building next-generation low-latency trading infrastructure.Ideal for readers with strong backgrounds in C++, GPU programming, and machine learning who want to push the boundaries of execution speed in algorithmic trading.…
Seller Inventory # 9798180331328
- Title
- Low-Latency AI Trading Kernels in C++20 : GPU Acceleration, FPGA Prototyping, and Execution Strategies for Deep RL and Neural PDE Policies
- Author
- James Preston
- Publisher
- Independently Published Jun 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798180331328
- Item weight
- 634 grams
- Dimensions
- 229x152x33 mm
Master the engineering of ultra-low latency AI trading systems with this technical deep dive into modern C++20, GPU acceleration, and FPGA prototyping.
This book explores the complete pipeline for building high-performance trading kernels capable of executing deep reinforcement learning (Deep RL) and neural PDE policies at extreme speeds. You will examine production-grade implementations using C++20 features, CUDA and GPU optimization techniques, and FPGA-based acceleration strategies designed for sub-microsecond decision cycles in live markets.
Key topics include:
- Modern C++20 architectures for low-latency kernel design
- GPU acceleration patterns for neural network inference in trading
- FPGA prototyping workflows for custom hardware acceleration
- Integration of Deep RL agents and neural PDE solvers into real-time execution engines
- Memory management, concurrency, and deterministic performance optimizations
Written for quantitative developers, high-frequency trading engineers, and AI systems programmers, this book provides detailed code examples, architectural diagrams, and practical implementation guidance for building next-generation low-latency trading infrastructure.
Ideal for readers with strong backgrounds in C++, GPU programming, and machine learning who want to push the boundaries of execution speed in algorithmic trading.
"Synopsis" may belong to another edition of this title.
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