Elevate your AI system performance capabilities with this definitive guide to unlocking peak efficiency across every layer of your AI infrastructure. In today’s era of ever-growing generative models, AI Systems Performance Engineering equips professionals with actionable strategies to co-optimize hardware, software, and algorithms for high-performance and cost-effective AI systems. Authored by Chris Fregly, a performance-focused engineering and product leader, this comprehensive resource transforms complex systems into streamlined, high-impact AI solutions.
Inside, you’ll discover step-by-step methodologies for fine-tuning GPU CUDA kernels, PyTorch-based algorithms, and multinode training and inference systems. You’ll also master the art of scaling GPU clusters for high performance, distributed model training jobs, and inference servers.
- Codesign and optimize hardware, software, and algorithms to achieve maximum throughput and cost savings
- Implement cutting-edge inference strategies that reduce latency and boost throughput in real-world settings
- Utilize industry-leading scalability tools and frameworks
- Profile, diagnose, and eliminate performance bottlenecks across complex AI pipelines
- Integrate full stack optimization techniques for robust, reliable AI system performance
Whether you’re an engineer, researcher, or developer, AI Systems Performance Engineering gives you a holistic roadmap for building resilient, scalable, and cost-effective AI systems that excel in both training and inference.
Author: Chris Fregly
Binding Type: Paperback
Publisher: O’Reilly Media
Published: 12/16/2025
Pages: 1058
Weight: 3.64lbs
Size: 9.19h x 7.00w x 2.08d
ISBN: 9798341627789
Language: English
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