AI Systems Performance Engineering
AI Systems Performance Engineering
Optimizing Model Training and Inference Workloads with Gpus, Cuda, and Pytorch
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Sign in or Sign up!- Release Date: 23/12/2025
- Barcode: 9798341627789
- Imprint: O'Reilly Media
- Publisher: O'Reilly Media

AI Systems Performance Engineering
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DESCRIPTION
Optimizing Model Training and Inference Workloads with Gpus, Cuda, and Pytorch Elevate your AI system performance capabilities with this definitive guide to maximizing efficiency across every layer of your AI infrastructure. In today's era of ever-growing generative models, AI Systems Performance Engineering provides engineers, researchers, and developers with a hands-on set of actionable optimization strategies. Learn to co-optimize hardware, software, and algorithms to build resilient, scalable, and cost-effective AI systems that excel in both training and inference. Authored by Chris Fregly, a performance-focused engineering and product leader, this resource transforms complex AI 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. The book ends with a 175+-item checklist of proven, ready-to-use optimizations.
Authored by Chris Fregly, a performance-focused engineering and product leader, this resource transforms complex AI 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.
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