FORBMAX’s Post

𝐄𝐦𝐩𝐨𝐰𝐞𝐫𝐢𝐧𝐠 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐌𝐨𝐝𝐞𝐫𝐧 𝐂𝐥𝐮𝐬𝐭𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 🧮 Modern cluster management tools redefine how organizations handle complex workloads across diverse environments. Tools like Rancher, Prometheus, and Slurm lead the charge, offering unparalleled scalability, real-time monitoring, and seamless orchestration for Kubernetes and HPC clusters. ☑️ 𝐖𝐡𝐲 𝐓𝐡𝐞𝐲 𝐌𝐚𝐭𝐭𝐞𝐫: 𝐑𝐚𝐧𝐜𝐡𝐞𝐫: Simplifies managing multi-cloud Kubernetes clusters, enhances security, and provides a user-friendly interface. 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬: Ensures robust observability with real-time alerts and metrics, vital for maintaining cluster health. 𝐒𝐥𝐮𝐫𝐦: Perfect for job scheduling, allowing efficient resource allocation for both small and large Linux clusters. ✳️ 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬 𝐃𝐫𝐢𝐯𝐢𝐧𝐠 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧: 𝐀𝐈 𝐖𝐨𝐫𝐤𝐥𝐨𝐚𝐝𝐬: Manage GPU-intensive training sessions effortlessly with NVIDIA Bright Cluster Manager. 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: Harness scalable solutions like IBM Spectrum LSF to optimize data-driven decision-making. 𝐇𝐲𝐛𝐫𝐢𝐝 𝐂𝐥𝐨𝐮𝐝 𝐅𝐥𝐞𝐱𝐢𝐛𝐢𝐥𝐢𝐭𝐲: Streamline deployment with Aspen Systems for hybrid and edge environments. 𝑪𝒍𝒖𝒔𝒕𝒆𝒓 𝒎𝒂𝒏𝒂𝒈𝒆𝒎𝒆𝒏𝒕 𝒕𝒐𝒐𝒍𝒔 𝒂𝒓𝒆 𝒕𝒉𝒆 𝒃𝒂𝒄𝒌𝒃𝒐𝒏𝒆 𝒐𝒇 𝒊𝒏𝒏𝒐𝒗𝒂𝒕𝒊𝒐𝒏, 𝒆𝒏𝒔𝒖𝒓𝒊𝒏𝒈 𝒔𝒎𝒐𝒐𝒕𝒉𝒆𝒓 𝒐𝒑𝒆𝒓𝒂𝒕𝒊𝒐𝒏𝒔 𝒂𝒏𝒅 𝒔𝒎𝒂𝒓𝒕𝒆𝒓 𝒔𝒄𝒂𝒍𝒂𝒃𝒊𝒍𝒊𝒕𝒚. 𝑹𝒆𝒂𝒅𝒚 𝒕𝒐 𝒆𝒍𝒆𝒗𝒂𝒕𝒆 𝒚𝒐𝒖𝒓 𝒊𝒏𝒇𝒓𝒂𝒔𝒕𝒓𝒖𝒄𝒕𝒖𝒓𝒆? #ClusterManagement #AI #Innovation #Kubernetes #TechTransformation #forbmax.ai #formedia.ai #fordata.ai #HPC

I had the pleasure of meeting with Tom McPherson last week, where he made an excellent point about supporting our IBM Power customers. He emphasized that we are "future-proofing" our clients with the latest technology. At IBM, we continuously evolve our solutions by understanding your current challenges and anticipating how they might change in the future. For instance, our latest S1012 server is designed for both edge computing and core business workloads. It allows you to reduce the IT footprint for business-critical applications and run transactional AI close to the data at the edge. By staying ahead of the curve, we ensure that your business remains resilient and competitive in an ever-changing technological landscape. #IBM #Power #S1012 #AI

#ibmpartners - Join us on 21 November to learn how #LinuxONE helps support a future of #sustainableIT Join IBM Z and LinuxONE Fellows and Senior Experts virtually on 21 November 2024, at 13:00 Eastern Time, to learn how you and your clients can:  - Leverage #IBM LinuxONE's #sustainability features to reduce #energyconsumption and physical footprint, positively impacting carbon emissions; - Optimize #resourceutilization and extend hardware lifespan through efficient #virtualization and containerization; - Adopt sustainable #AI practices with minimal disruption to business operations through thoughtful processing location choices and optimized #infrastructure design. https://lnkd.in/eEYkAszS

**Did you know?** 💡 In 1980, IBM introduced the first 1GB hard drive. It weighed over 500 pounds and cost a staggering $40,000! Today, we can store far more data on a tiny microSD card that costs just a few dollars and weighs less than a gram. 📈💾 It's incredible to see how far technology has come in just a few decades. What other tech advancements have amazed you? Share your thoughts below! 👇 #TechHistory #Innovation #DataStorage #TechFacts

The field of generative AI is expanding faster than ever, with new applications emerging every day. But success in this field requires an information architecture that allows for data agility, mobility, and resiliency. Enter IBM Storage Scale, a software-defined accelerated data platform capable of supporting multiple compute platforms: IBM Z, Power, x86, Kubernetes and OpenShift, to drive next-gen workloads. Our vertically integrated, all-flash hardware platform (Storage Scale System 6000) is capable of 310 GB/sec and up to 13M IOPS ensuring that storage is never a bottleneck when conducting training operations across dozens of GPUs or supporting large teams of data scientists. IBM Storage Scale is an essential tool for any organization looking to stay competitive in today's rapidly evolving technological landscape. Unlock the full potential of your data and stay ahead of the curve with IBM Storage Scale. #IBM #AI #DataAgility #DataScience #TechnologyGrowth

So great to be here with SiliconANGLE & theCUBE talking about disrupting traditional storage concepts and delivering innovations to help any company get the most from their data.

Just another model on the block? 🤔 We've seen many releases this year about another 0.5% or 1% accuracy improvement... honestly, it doesn't matter until its 100% from human eyes hahaha 🤓, so here's why IBM's latest model series, #Granite3 𝗼𝗳𝗳𝗲𝗿𝘀 𝗮 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝘁𝗲𝗱 𝘃𝗶𝘀𝗶𝗼𝗻 𝗳𝗼𝗰𝘂𝘀𝗶𝗻𝗴 𝗼𝗻 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝘀𝗰𝗮𝗹𝗲 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘀𝗮𝗯𝗹𝗲: 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝘃𝗮𝗹𝘂𝗲 𝘁𝗼𝗱𝗮𝘆 𝗶𝘀 𝘁𝗼 𝗳𝗶𝗻𝗲 𝘁𝘂𝗻𝗲 𝗮 𝗯𝗮𝘀𝗲 𝗺𝗼𝗱𝗲𝗹 𝘄𝗶𝘁𝗵 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗱𝗮𝘁𝗮, the smaller sizes, 8B and 2B, open weights, uncapped legal indemnity for third party IP claims, transparency in training data lineage and associated safety guardrail models makes Granite an ideal base model for customisation 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝘁: it matches similar size open source models on general tasks whilst 𝗲𝘅𝗰𝗲𝗹 𝗮𝘁 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗱𝗼𝗺𝗮𝗶𝗻𝘀 𝘀𝘂𝗰𝗵 𝗮𝘀 𝘀𝗮𝗳𝗲𝘁𝘆, 𝗰𝗼𝗱𝗲, 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝗰𝗮𝗹𝗹𝗶𝗻𝗴, 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴, 𝗺𝘂𝗹𝘁𝗶𝗹𝗶𝗻𝗴𝘂𝗮𝗹, 𝗥𝗔𝗚 𝗮𝗻𝗱 𝗺𝗼𝗿𝗲 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: 1B and 3B MoE models (400M and 800M active parameters at inference) are 𝗶𝗱𝗲𝗮𝗹 𝗳𝗼𝗿 𝗼𝗻-𝗱𝗲𝘃𝗶𝗰𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁, 𝗖𝗣𝗨 𝘀𝗲𝗿𝘃𝗲𝗿𝘀 𝗮𝗻𝗱 𝗲𝘅𝘁𝗿𝗲𝗺𝗲𝗹𝘆 𝗹𝗼𝘄 𝗹𝗮𝘁𝗲𝗻𝗰𝘆 All trained on Blue Vela, IBM's super compute cluster, 𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗯𝘆 𝟭𝟬𝟬% 𝗿𝗲𝗻𝗲𝘄𝗮𝗹 𝗲𝗻𝗲𝗿𝗴𝘆 - 𝗲𝗻𝗲𝗿𝗴𝘆 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝗮𝗹 𝘀𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘀𝗵𝗼𝘂𝗹𝗱 𝗯𝗲 𝗽𝗿𝗲-𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻 𝘁𝗼 𝗮𝗻𝘆 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗜. #Granite #EnterpriseAI #InstructLab

🌟Flashback Friday - Did you miss this article by IBM Research ? ❗Accessing #ML models that instruct individuals where to go in a disaster, like in the PER case, means people’s devices need to be "served", i.e., be available as a remote service. 🖇️For many devices to access the model over a short period of time in a timely manner, 1 simple server is likely not enough and many hardware resources need to be distributed over many machines. 🦾The #extracteuproject is leveraging the #Kubernetes ecosystem, specifically KServe and in its more sophisticated mode – serverless KServe to provide user-friendly and timely solutions Learn how👉https://lnkd.in/edbTJszb

Find out best practices for enterprises to utilize full stack accelerated computing, including pre-trained models, acceleration libraries, and custom frameworks. Read the article on LinkedIn.

As AI adoption becomes more common in organizations, having the right storage infrastructure is crucial. IBM Storage has been collaborating with NVIDIA to develop NVIDIA DGX POD reference architectures that incorporate IBM Storage Scale storage and NVIDIA DGX systems, which are essential for supporting the large datasets that fuel AI model. 💰 Optimizing Total Cost of Ownership (TCO) for AI infrastructure is crucial for enterprises looking to stay competitive in today's market. By eliminating unnecessary data copies and associated data management, enterprises can minimize TCO. The caching functionality also speeds up productivity by prefetching required data and evicting unused data to create space for active data, reducing manual efforts involved in data movement. Additionally, customers can mix analytics, training, and inference jobs on every DGX system in a cluster, making it a universal system for AI. The data orchestration functionality offers additional support from the storage side for maintaining agility by bringing in the right data for the right workload in the high-performance storage tier. Stay ahead of the game with these cutting-edge AI infrastructure solutions. For example: 😎 JUPITER will be the first European supercomputer of the Exascale class and will be the system with highest compute performance procured by EuroHPC JU,which includes multiple Petascale and Pre-Exascale systems throughout Europe. 21 Petabyte Flash Module is provided based on the IBM Storage Scale software and a corresponding storage appliance based on IBM ESS 3500 building blocks. https://lnkd.in/eU4PFjQv #AI #NVIDIA #AI #TCO #Productivity #Agility #DataOrchestration #DGX