Principal Program Manager Telecom & Data Center Alliance Partners @OracleCloud FastConnect Sales Engineering. Business Development. Views are my own. SMM @redbullracing
Oracle integration latest Nvidia platform to OCI Supercluster and Compute adopting NVIDIA GB200 Grace Blackwell Superchip and the B200 Tensor Core GPU. Collaboration between Oracle and Nvidia deploying Nvidia DGX Cloud on OCI, introducing its new GB200
Discover challenges faced by organizations when implementing Stable Diffusion XL and how Let's Enhance overcomes them using Google Cloud G2 instance with NVIDIA L4 Tensor Core GPUs, #TensorRT, and Triton Inference Server for improved solutions: https://nvda.ws/4bUEHt3
Established Technology Professional | Relationship Focused Leader | 27+ Year IT Veteran | Passion for People | Outdoor Enthusiast
🌟 Just when you thought simulations couldn't get any larger - Altair and Google Cloud shattered expectations! We ran a billion-particle simulation using Altair® EDEM™ on a single A3 VM with 8 NVIDIA H100 GPUs, and the results were groundbreaking. Learn how GPUs are transforming material simulations and revolutionizing industries. Check out the mind-blowing experiment here: [Read more](https://ift.tt/YjW9d3e) 🚀 #GCP #GoogleCloud #66degrees #cloud #cloudcomputing
CRO @Aethir | Interactive Technology and Games Executive | Start-up Advisor | Mixed Reality | AI | Web3 | DePIN
"Aethir brings its network of over 40,000 enterprise-grade GPUs, including more than 8,000 NVIDIA H100s, to the partnership. This represents a total of 170,000 TFLOPS of compute power. Meanwhile, Theta’s Edge Network comprises one of the world’s largest clusters of distributed GPU computing power, with a combined total of approximately 80 PetaFLOPS, equivalent to 250 Nvidia A100s. By shifting from centralized to decentralized network infrastructure, Aethir and Theta aim to reduce latency and provide best-in-class GPU resources to end-users, regardless of their physical location. The decentralized model offers superior GPU efficiency by pooling power from multiple GPUs, maximizing usage, and reducing costs for clients." #decentralizedcompute #gpu #disruption https://lnkd.in/gZF6kwbe
Cloud & GPU @ Vultr | NVIDIA Elite Partner | World's Largest Bootstrapped Cloud Provider | Ex-SADA | Ex-Sumo Logic | Ex-Blue Jeans | Ex-LinkedIn
Thrilled to share how HEAVY.AI using NVIDIA's GH200 GPU on #Vultr's Cloud is revolutionizing real-time data visualization and analytics—10.8 billion records and counting! #CloudGPU #Vultr #DataVisualization #RealTimeAnalytics #NVIDIA #HEAVYAI"
We're seeing incredible performance running the HEAVY.AI GPU-accelerated analytics platform on the NVIDIA GH200 on Vultr Cloud. Check out 10.8 billion records of US AIS (ship traffic) data, all running in HeavyDB on a single GH200 GPU and visualized in Heavy Immerse. With ~4TB/sec of on-GPU bandwidth, and 900GB/sec of blazing fast NVLink between the GPU and ARM CPU, Grace Hopper is a game changer for real-time analytics and visualization of gigantic datasets. More benchmarks and demos to come, and special thanks to both NVIDIA and Vultr for all their support.
App Hosting, Cloud Services, Systemhaus, KI - IT von A-Z für die Unternehmen von morgen
Dear network: who's running AI/LLM stuff AT HOME - i.e. having 1 or more RTX3090+ in a rack- or desktop-case? We're currently investigating if we can make self-hosted GPUs available for GPT-based workloads on our GPU Cloud at ayedo and I need to bounce a few thoughts with people running GPUs at home. After all, with good enough latency, who says a GPU powering Ollama needs to run in a datacenter? 😝 #kubernetes #nvidia #llm #ai
BIG GEOSPATIAL DATA and SUPER FAST. 10.8 BILLION records of ship traffic data. Queries refreshing instantaneously with HEAVY.AI on a single Nvidia GH200 GPU. #businessintelligence #analytics #data
We're seeing incredible performance running the HEAVY.AI GPU-accelerated analytics platform on the NVIDIA GH200 on Vultr Cloud. Check out 10.8 billion records of US AIS (ship traffic) data, all running in HeavyDB on a single GH200 GPU and visualized in Heavy Immerse. With ~4TB/sec of on-GPU bandwidth, and 900GB/sec of blazing fast NVLink between the GPU and ARM CPU, Grace Hopper is a game changer for real-time analytics and visualization of gigantic datasets. More benchmarks and demos to come, and special thanks to both NVIDIA and Vultr for all their support.
On-device AI is just better. It is advancing and will continue to close the gap until it is good enough to do much of what we may require. It is already better for: * Privacy: Your data stays on your device. * Speed: No waiting on the cloud for results. * Reliability: Doesn't need the internet. * Customization: Tailored experiences just for you. * Cost-effective: No need to line the pockets of cloud providers. * Better for the environment: Reduced energy consumption. Cloud-based AI will always have a role to play now and in the future, but I believe on-device + open source AI is better for people and society to use whenever possible. This option will become increasingly viable also as research continues to advance.
I told you 2024 is gonna be the year of on-device AI and small models. Qualcomm just released 84 AI and ML models for Snapdragon. Yet another SoC option with unified memory for inferencing LLMs locally, now we just need better open-source runtime. Inferencing in the cloud on behemoth GPUs is so 2022. We have all the idle dark compute in our pockets, on our desks on our edge computing. We have all the open source tools and knowledge to use it better now. Make sure you own your AI. AI in the cloud is not aligned with you; it's aligned with the company that owns it.
Need computing power for your AI, 3D rendering, HPC projects ? Follow me to build it | Cloud GPU for companies | CEO @Arkane Cloud
It's time. Today, we open reservation to rent GB200 cluster. We can build your superPod for your ambitious AI & HPC project! Get 72 NVIDIA Blackwell GPUs connected as one to build a massive GPU. Few spec : ♦ 1.4 exaFLOPS of AI performance ♦ 30 terabytes (TB) of fast memory ♦ 130 terabytes per second (TB/s) of bidirectional GPU bandwidth. Performance on different use-cases : 🔺 x2.5 more performance than H100 on LLama3 70B. 🔺 x4 for training 1.8T MOE than H100 Why Choose Arkane Cloud? High Performance: Get last generation of GPU for your project and get decrease your time to market! Flexibility: Rent clusters as needed, optimizing your resource utilization. Get commitment that suit for your project. Expert Support: We can help you to find and design the cluster you need for your project. Reserve your GB200 cluster for rental now to get your allocation! Comment this post if you need more information. https://lnkd.in/dNaVEFKe
🚀 The Need for Speed is Growing! 🚀 Julien Gauthier is about to introduce a range of hardware solutions that seemed unimaginable when I started my career in IT. What's even more astounding is that it's now not just technically feasible—it's seems a necessity for his customers. These powerful machines are designed to fine-tune and host enterprise AI solutions, marking a significant milestone in the evolution of AI technology. The essence to me is that Enterprise AI solutions are on the rise, and we are likely to see many alternatives to the omnipresent solutions from well known market defining vendors.
Need computing power for your AI, 3D rendering, HPC projects ? Follow me to build it | Cloud GPU for companies | CEO @Arkane Cloud
It's time. Today, we open reservation to rent GB200 cluster. We can build your superPod for your ambitious AI & HPC project! Get 72 NVIDIA Blackwell GPUs connected as one to build a massive GPU. Few spec : ♦ 1.4 exaFLOPS of AI performance ♦ 30 terabytes (TB) of fast memory ♦ 130 terabytes per second (TB/s) of bidirectional GPU bandwidth. Performance on different use-cases : 🔺 x2.5 more performance than H100 on LLama3 70B. 🔺 x4 for training 1.8T MOE than H100 Why Choose Arkane Cloud? High Performance: Get last generation of GPU for your project and get decrease your time to market! Flexibility: Rent clusters as needed, optimizing your resource utilization. Get commitment that suit for your project. Expert Support: We can help you to find and design the cluster you need for your project. Reserve your GB200 cluster for rental now to get your allocation! Comment this post if you need more information. https://lnkd.in/dNaVEFKe
Established Technology Professional | Relationship Focused Leader | 27+ Year IT Veteran | Passion for People | Outdoor Enthusiast
🚀 Exciting news! 🚀 GKE can now automatically install NVIDIA GPU drivers, making it even easier to utilize GPUs in Kubernetes. No more manual setup, just seamless integration for accelerated compute. Take a look at the blog post to learn more: [Automatic driver installation simplifies using NVIDIA GPUs in GKE](https://ift.tt/BnVfeYr) #GKE #GPUs #NVIDIA #Kubernetes #AI #MachineLearning #GCP #GoogleCloud #66degrees #cloud #cloudcomputing
