{"product_id":"b0h7qxmqcm","title":"GPU Kernel Engineering for LLM Inference: CUDA, Triton, and Flash Attention Optimization for High-Throughput AI Production Systems (AI Infrastructure, Hardware \u0026 Compiler Engineering Series)","description":"\u003cp\u003eMaster GPU Kernel Engineering for Production LLM Inference In the high-stakes world of AI production, the bottleneck isn't model architecture—it's execution efficiency.  GPU Kernel Engineering for LLM Inference  is the definitive engineering guide designed to close the gap between framework-level PyTorch code and hardware-optimal hardware performance.\u003c\/p\u003e\n\n\u003cp\u003eWritten specifically for machine learning engineers, systems software developers, and performance engineers, this practical manual provides deep, production-ready blueprints for building high-throughput AI serving infrastructure. You will move past theoretical concepts and dive straight into raw hardware-level optimizations that top AI teams use to slash latency and reduce infrastructure costs.\u003c\/p\u003e\n\n\u003cp\u003eWhat You Will Master: Custom CUDA Kernels:  Write and optimize high-performance CUDA C++ kernels tailored specifically for modern Transformer workloads. Flash Attention 2 \u0026amp; 3:  Implement advanced IO-aware attention algorithms with Hopper-specific asynchronous memory and Tensor Core operations. Triton Development:  Build optimized fusion kernels for layer normalization, activation functions, and positional encodings using Python-level Triton. Quantization \u0026amp; GEMM:  Develop high-throughput INT8, INT4, and weight-only quantized GEMM kernels for optimized memory footprints. PagedAttention \u0026amp; KV-Cache:  Design vLLM-style virtual memory management kernels to eliminate memory fragmentation. Multi-GPU Scaling:  Coordinate tensor-parallel all-reduce operations with custom NCCL collectives to scale seamlessly across cluster nodes. Nsight Profiling:  Locate hardware bottlenecks using Nsight Systems and Nsight Compute. Stop relying on out-of-the-box configurations. Equip yourself with the systems engineering skills required to build the next generation of high-speed, cost-efficient AI infrastructure. Learn to build kernels that run at the absolute physical limits of NVIDIA silicon.\u003c\/p\u003e","brand":"ANT","offers":[{"title":"Ebook","offer_id":67924588822773,"sku":"YSL53236","price":5.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/8774\/8597\/files\/71uGHe8oRvL._SY1500.jpg?v=1793673281","url":"https:\/\/www.newbooks.store\/products\/b0h7qxmqcm","provider":"NewBooks","version":"1.0","type":"link"}