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AI Systems Performance Engineering Optimizing Model Training and Inference Workloads with Gpus, Cuda, and Pytorch-Fast Shipping

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Description

Elevate your AI system performance capabilities with this definitive guide to unlocking peak efficiency across every layer of your AI infrastructure. In todays 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, youll discover step-by-step methodologies for fine-tuning GPU CUDA kernels, PyTorch-based algorithms, and multinode training and inference systems. Youll 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 youre 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: OReilly 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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