Unlock the potential of custom large language models (LLMs) with Azure AI's powerful infrastructure. This session explores Azure Machine Learning and Azure AI infrastructure, including ND H100 and H200 series. Learn how to leverage distributed training to enhance scalability, performance, and efficiency. We'll cover practical techniques for optimizing LLM training workflows, ensuring you can harness the full potential of Azure AI to accelerate your AI projects.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * John Lee * Ben Levine * Yogi Pandey * Alejandra Rico

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK120 | English (US) | AI

MSIgnite

As companies depend more and more on their enterprise software for daily operations, they require highly available systems. JD Edwards EnterpriseOne has long enabled their software with the IBM High Availability Cluster Multi-Processing (HACMP) product for high availability. This IBM Redbooks publication describes the IBM HACMP/Enhanced Scalability (HACMP/ES) Version 4.5 solution to certify JD Edwards EnterpriseOne 8.9 in an IBM AIX high availability environment. This book also describes HACMP/ES Version 5.1. It explains how to install and tune HACMP/ES, as well as reviews the setup steps to enable JD Edwards EnterpriseOne for HACMP/ES. While writing this book, we conducted tests to simulate that the failures and observations made to ensure that the high availability environment performed properly. The results of these tests are also documented. This book highlights and explains those characteristics that are specific to JD Edwards EnterpriseOne. It contains significant window examples and worksheets to help facilitate an easy step-by-step installation process. It does not replace the extensive installation and administration documentation that is already available for HACMP/ES.