{"product_id":"supercomputing-for-artificial-intelligence-foundations-architectures-and-scaling-deep-learning-workloads-paperback","title":"Supercomputing for Artificial Intelligence: Foundations, Architectures, and Scaling Deep Learning Workloads - Paperback","description":"\u003cp\u003eby \u003cb\u003eJordi Torres\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWhen code is cheap, performance is expensive.\u003c\/b\u003e\u003cbr\u003eSupercomputing for Artificial Intelligence is a systems-oriented guide to understanding what really happens when AI code runs at scale.\u003cbr\u003eLearn how to train deep learning models and LLMs on GPUs, clusters, and supercomputers-and how to reason about performance, scalability, and cost.\u003c\/p\u003e\u003cp\u003eSupercomputing for Artificial Intelligence is a practical, systems-oriented guide to mastering the infrastructures, tools, and execution trade-offs involved in scaling deep learning systems-from neural networks to large language models (LLMs).\u003c\/p\u003e\u003cp\u003eDesigned for graduate students, AI researchers, data scientists, and engineers, this book bridges the gap between high-performance computing (HPC) and real-world AI applications. In an era where AI tools can generate entire training pipelines in minutes, the real engineering challenge has shifted from writing code to understanding performance, scalability limits, and cost. Whether you're working in academia, industry, or exploring advanced AI on your own, you'll find clear explanations and hands-on examples built around tools like PyTorch, CUDA, MPI, SLURM, and multi-GPU distributed training.\u003c\/p\u003e\u003cp\u003eWith over 800 pages of rigorously tested content, this book develops the ability to reason about large-scale AI training through: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eThe foundations of supercomputing and its role in AI workloads\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003ePractical GPU programming with CUDA and distributed systems\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eParallel programming with MPI on modern clusters\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eEfficient training of neural networks, CNNs, and Transformers\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003ePerformance optimization for deep learning at scale\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eDistributed training with PyTorch DistributedDataParallel (DDP)\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eBuilding and scaling LLMs using real biomedical and NLP datasets\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eJupyter, Google Colab, and Hugging Face workflows\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eDeployment and inference strategies for modern LLMs\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eAll source code, configuration files, and job scripts are available in a public GitHub repository. The material is field-tested through years of teaching and research at the Barcelona Supercomputing Center, and can be applied on local GPU setups, cloud platforms, and HPC clusters.\u003c\/p\u003e\u003cp\u003eThis book is ideal for: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eInstructors looking for practical material for AI and HPC courses\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eStudents and professionals wanting to learn how to run AI at scale\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eEngineers transitioning from standard AI workflows to distributed environments and seeking system-level judgments\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eResearchers working on LLMs and interested in reproducible pipelines\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eDo I need a supercomputer to use this book? Not at all. While some examples are run on large systems like MareNostrum, some code is designed to scale-from a single GPU to a full HPC node. You'll find guidance for running experiments in Google Colab and containerized environments. The emphasis throughout is not on maximum scale, but on understanding when scaling makes sense-and when it does not.\u003c\/p\u003e\u003cp\u003eWhether you're teaching AI, training models at scale, or simply curious about the invisible infrastructure powering today's most powerful AI systems, this book is your companion to understanding and leveraging supercomputing for artificial intelligence.\u003c\/p\u003e\u003cp\u003eThis is not a book about writing code faster. It is about understanding what happens when that code runs-on GPUs, across nodes, under real resource constraints.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWhat's inside: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003e800+ pages of real-world content tested in supercomputing classrooms\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eHands-on examples with PyTorch, CUDA, MPI, and SLURM\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eFull GitHub access with ready-to-run scripts and datasets\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eWorkflows adapted for Google Colab, and HPC clusters\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 804\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.6 x 9.69 x 7.44 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 30, 2025\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":71754089758973,"sku":"9798319328359","price":74.48,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/3414\/0157\/files\/ck6orzo1Xe9798319328359.webp?v=1793339530","url":"https:\/\/booktolia.com\/products\/supercomputing-for-artificial-intelligence-foundations-architectures-and-scaling-deep-learning-workloads-paperback","provider":"booktolia","version":"1.0","type":"link"}