TensorOpera AI’s Post

#Tailscale is built on #Wireguard. It handles all of the key rotation, the coordination between instances on the user’s behalf. It helps users traverse complicated networks. From a Kubernetes perspective, Tailscale enables cross cluster communication both in different regions or in the same region. It enables a user to expose like services and ingresses or workloads to internal users with a zero trust approach. So you can tag different devices and limit who's able to access those things. It takes away the complexity at the routing level. Communicating between clusters is a common problem in the AI space where GPUs are in short supply. Tailscale makes it easier to cross connect cloud providers to get access to resources such as GPUs. #kubecon

***THE BEST AI INFRASTRUCTURE*** Run the most demanding AI workloads faster, including generative AI, computer vision, and predictive analytics. Use Oracle Cloud Infrastructure (OCI) Supercluster to scale up to 32,768 GPUs today and 65,536 GPUs in the near future. #GPU #AIInfrastructure #OCI

At Oracle Cloud Infrastructure (OCI) we focus on price-to-performance of GPU hardware on any new product launches. Here is an example on benchmarking a scenario that is very close customer production use cases with LLama 2 70B serving at scale. AMD MI300X continues to impress us with a powerful hardware & software shaping up for most demanding workloads. https://lnkd.in/gVQgbepz #AMD #OCI #LLM #GenerativeAI #MI300X

Learn all about enterprise AI deployments in the cloud in our new blog post, including info about: 🔷 NVIDIA GB200 Blackwell release 🔷 State-of-the-art liquid cooling in the data center 🔷 DPU's and BMC observability 🔷 Software for 1000+ server clusters Check out the Jacob Yundt-authored post below 👇 https://hubs.la/Q02Ln2TD0

Check out the new article from Adam Armstrong with TechTarget on our Aries #PCIe/#CXL Smart Cable Modules (SCMs). This article goes into more detail on how our Aries SCMs will enable CXL-attached memory and multi-rack GPU clustering for #cloud and #AI. Read now:

Learn How to run LLMs on AMD GPUs.

🚀 Elevate Your Compute Power with GPUs! 🚀 🔥 Embrace Peak Performance: Unleash the true potential of your computing tasks with the unparalleled power of Graphics Processing Units (GPUs). 💡 Whether you're into AI, deep learning, or high-performance computing, GPUs are the game-changers you've been waiting for! 💪 Why GPUs? ✨ Lightning-Fast Processing: Accelerate your workloads and enjoy seamless, rapid computations. ✨ Deep Learning Dynamo: Propel your AI projects to new heights with GPU-driven parallel processing. ✨ Versatility Unleashed: From gaming to data analytics, GPUs redefine multitasking prowess. 💡 Dive into the GPU Advantage: 🚀 Cutting-Edge Technology: Stay ahead with the latest GPU innovations. 🌐 Global Impact: Revolutionize industries from healthcare to finance with accelerated data analysis. 🌟 Ready to Upgrade? Discover the transformative power of GPUs - where speed meets precision, and innovation knows no bounds. 💻✨ Let's shape the future together! 🚀 #GPU #ComputingPower #Innovation #TechUpgrade #hellopaperspace https://bit.ly/49D9wRf

Really interesting webinar earlier today from NVIDIA covering considerations for deploying #generativeAI in production. Nice job Bethann Noble and Neal Vaidya! Some takeaways: 1. #genai is moving from experimentation to production quickly, and they provided some good tips on building RAG frameworks and pipelines, and good best practices in general. 2. Interesting insight that the workloads are going to shift from 80% training today to 80% inference in a few years (I rounded and simplified). 3. Arguably, keeping GPUs 100% utilized for inference is going to be more important, because your customers (either internal or external) are waiting. Hammerspace delivers fast performance to keep GPUs fully utilized, and brings your data to your GPU resources even if they are in the cloud. Learn more about how we are reducing latencies and increasing throughput in NVIDIA environments.

Joining the #AIConference next week and need fast, dependable GPU infrastructure at your fingertips? Look no further! Whether you're building cutting-edge AI models or scaling your ML workflows, GMI Cloud has you covered. 💼 Let’s connect! Reach out here on LinkedIn or email sales@gmicloud.ai to schedule a time to meet and get a personal demo of our full-stack GPU platform. Don’t miss out on optimizing your AI projects with high-performance GPUs! #AIConference #SF #GPUCloud #AIInfrastructure #CloudComputing #GPUPower

"The Need for AI Infrastructure Solutions to Focus on GPU Optimization" Generative AI is reshaping the IT landscape, making GPUs more essential than ever. As Moore’s Law slows down and edge computing advances, GPUs have become vital for handling the demands of AI and high-performance computing.With their high demand and limited supply, organizations are investing heavily in GPUs for both on-premises and public cloud infrastructure. But integrating GPUs into existing infrastructure brings new challenges. Traditional IT setups were simple and standardized, but GPUs require a more strategic approach. A recent report highlights that 15% of organizations use less than half of their GPUs, indicating potential mismatches between available resources and actual workloads. To optimize GPU utilization, companies must enhance their infrastructure management practices. This means smart provisioning, efficient load balancing, and possibly leveraging public cloud GPU resources. Updating enterprise architecture to address these complexities is crucial for fully leveraging the power of AI and ensuring effective resource use. Source: https://lnkd.in/gwmavZJj #AI #F5 #GPUOptimization