NVIDIA today said it is working with manufacturing partners to design and build factories that will produce NVIDIA AI supercomputers — i.e., “AI factories” — entirely in the United States… NVIDIA said that within four years, it plans to produce up to half a trillion dollars worth of AI infrastructure in the U.S. through partnerships ….
Nvidia H100s GPUs Available on IBM Cloud for AI and HPC
October 1, 2024 by
Oct. 1, 2024 — IBM announced the availability of NVIDIA H100 Tensor Core GPU instances on IBM Cloud. It joins IBM Cloud’s existing lineup of accelerated computing offerings for enterprise’s AI implementation. IBM said that despite increasing interest in generative AI, only 39 percent of organizations surveyed say they are currently implementing or operating gen AI […]
CGG Launches AI Cloud Solution with Nvidia for AI and HPC Workloads
May 9, 2024 by
Paris, May 9, 2024 — Technology and HPC company CGG has announced the launch of its AI Cloud, designed for data-intensive industries, including life sciences, digital media, manufacturing and geoscience, that seek to optimize and accelerate their demanding and resource-heavy AI workloads. CGG’s new AI Cloud solution combines the latest high-performance architecture, including cutting-edge Nvidia […]
Accelerated HPC for Energy Efficiency with AWS and NVIDIA
February 20, 2024 by
Many industries are starting to run HPC in the cloud. Find out how GPU-accelerated compute, from AWS and NVIDIA, is helping organizations run HPC workloads and AI/ML jobs faster, in a more energy-efficient way.
Taking on NVIDIA: AMD Announces Availability of MI300 GPU Accelerators
December 6, 2023 by
After years of NVIDIA having its dominant way in the GPU AI chip market — a market that has exploded over the last 12 months with the emergence of generative AI — AMD today announced the availability of the long-awaited and much previewed MI300X accelerator chip (pictured here) that AMD intends to be a worthy competitor with NVIDIA’s H100….
Flare Gas Data Center Company Crusoe Picks HPE for Green GenAI
October 17, 2023 by
Hewlett Packard Enterprise (NYSE: HPE) today announced its HPE Cray supercomputers were selected by Crusoe, a builder of modular data centers, to power new cloud services designed to drive sustainable computing for generative AI and other compute-intensive workloads. Crusoe will leverage custom HPE Cray XD supercomputers to train and tune large-scale AI models….
Google Launches AI Supercomputer Powered by Tens of Thousands of NVIDIA H100 GPUs
May 11, 2023 by
If a computer’s intelligence can be anthropomorphized, then an AI supercomputer that can scale to 26,000 GPUs (26 exaFLOPS AI throughput) is at the head of the class. That’s the case with Google’s new A3 GPU supercomputers for Google Cloud, introduced at the Google I/O 2023 conference. Google said A3 GPU VMs are designed to […]
Cloud Company Vultr Announces Availability of NVIDIA H100s and Data Science Partnerships with Anaconda and Domino Data Labs
March 21, 2023 by
March 21, 2023 — WEST PALM BEACH, Fla. — Vultr, cloud computing company, today announced availability of the NVIDIA HGX H100 for accelerated computing. Vultr also announced today a three-way strategic alliance with leading data science and machine learning operations platforms Anaconda Inc. and Domino Data Lab designed to accelerate the work of MLOps engineers. The NVIDIA […]
DDN Announces Compatibility with NVIDIA DGX H100 and Lambda Partnership
March 21, 2023 by
CHATSWORTH, Calif. – March 21, 2023 – AI and multi-cloud data management company DDN today announced compatibility with the next generation of NVIDIA DGX systems, each with eight NVIDIA H100 Tensor Core GPUs. NVIDIA DGX H100 supercomputers are the fourth generation of NVIDIA’s purpose-built AI systems and designed for the most taxing training workloads, such as natural language processing […]
NVIDIA Hopper GPUs Expand Reach as Demand for AI Grows
March 21, 2023 by
NVIDIA and key partners today announced the availability of new products and services featuring the NVIDIA H100 Tensor Core GPU — the powerful GPU for AI — to address rapidly growing demand for generative AI training and inference.
