Published on 30 March 2026
ISBN-10: 0738462578
ISBN-13: 9780738462578
IBM Form #: SG24-8592-00
Authors: Tim Simon, Harshitha C, Anjil Reddy Chinnapatlolla, Ricardo Contreras, Florian Dahlitz, Abdul Haleem, Blake Hoskinson, Bijay Dev K M, Henrik Mader, Manish Mukul, Arnold Ness, Nnamdi Okore-Affia II, Praveen Kumar Pandey, Manvanthara Puttashankar, Daniel Schenker, Vaibhav Shandilya, David Spurway, Rajalakshmi Srinivasaraghavan, Borislav Stoymirski, Henry Vo and Jack Woehr
This IBM Redpaper publication presents the IBM® next-generation platform for enterprise artificial intelligence (AI) and shows how IBM Power11 strengthens on-chip acceleration, system design, and hybrid AI deployment. It outlines key AI concepts and industry trends, which emphasize the need for secure, high-performance inference close to mission-critical data.
A major highlight is IBM Spyre™ PCIe Gen5 x16 AI Accelerator Adapter (IBM Spyre Accelerator), which is a new reduced-power Peripheral Component Interconnect Express (PCIe) accelerator that is designed for scalable AI inference. With a highly parallel architecture and support for modern AI numerics, Spyre enables efficient running of large language models (LLMs), embedding, retrieval-augmented generation (RAG), and other enterprise AI workloads. Integrated with Red Hat AI and vLLM, it delivers on-premises AI with predictable performance and data-sovereign control.
The publication also addresses end-to-end lifecycle requirements, such as security, governance, machine learning operations (MLOps), and industry use cases, and shows how Power11 and Spyre support regulated, data-intensive environments. Combined with IBM's broader software and open-source ecosystem, the platform provides a complete blueprint for deploying enterprise-grade AI on IBM Power.
Chapter 1. Introducing artificial intelligence on IBM Power11
Chapter 2. Use cases and industry applications
Chapter 3. On-chip acceleration
Chapter 4. IBM Spyre Accelerator
Chapter 5. Artificial intelligence workload optimization on IBM Power11
Chapter 6. Artificial intelligence and security
Chapter 7. Tools, frameworks, and ecosystem