{"product_id":"b0h5nqppx7","title":"LLM INFERENCE ENGINEERING: Optimizing Large Language Models on NVIDIA GPUs","description":"\u003cp\u003eA comprehensive technical guide to building and deploying production LLM inference systems. Covers transformer architecture through AI factory design, with deep dives into NVIDIA GPU architectures (H100, B200, Grace Hopper), continuous batching, model optimization, and rack-scale deployment. Designed for Solution Architect candidates and AI infrastructure engineers.\u003c\/p\u003e\n\n\u003cp\u003eKey Topics:  Transformer architecture • KV caching • FlashAttention • Continuous batching • GPU memory hierarchy • vLLM \u0026amp; TensorRT-LLM • Grace Hopper \u0026amp; Blackwell • Model parallelism • Production serving • AI datacenter design\u003c\/p\u003e\n\n\u003cp\u003eUnique Features:\u003c\/p\u003e\n\n\u003cp\u003e100+ interview questions with detailed answers Real-world TCO analysis and cost optimization GPU-specific optimization techniques throughout 17 comprehensive chapters covering fundamentals to advanced deployment Production-ready patterns and best practices Target Audience:  AI infrastructure engineers, Solution Architect candidates, ML platform engineers and technical architects building LLM systems at scale.\u003c\/p\u003e","brand":"ANT","offers":[{"title":"Ebook","offer_id":52834352759000,"sku":"YSL55609","price":5.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0835\/3356\/2072\/files\/516VJjIvCvL._SY1500.jpg?v=1793259089","url":"https:\/\/www.bookmebay.com\/products\/b0h5nqppx7","provider":"BookMebay","version":"1.0","type":"link"}