Oracle Cloud Infrastructure (OCI) Supercluster provides ultrafast cluster networking, HPC storage, and OCI Compute bare metal instances. OCI Supercluster is ideal for training generative AI, including conversational applications and diffusion models. With support for up to tens of thousands of NVIDIA GPUs, OCI Compute bare metal instances and VMs can power applications for computer vision, natural language processing, recommendation systems, and more.
Oracle and NVIDIA partner to speed AI adoption for enterprises (2:06)
Deploy up to tens of thousands of GPUs per cluster for much greater scalability than similar offerings from other providers.
Reduce the time needed to train AI with simple Ethernet network architecture that provides ultrahigh performance at massive scale.
Get engineering help with solution architecture, networking, security, auditing, onboarding, application migration, and much more.
Each OCI Compute bare metal instance is connected using OCI’s ultralow-latency cluster networking, which can scale up to tens of thousands of NVIDIA H100 or A100 GPUs in a single cluster. These instances use OCI’s unique high performance network architecture, which leverages RDMA over Converged Ethernet (RoCE) v2 for microseconds of latency between nodes and near line-rate bandwidth.
OCI’s implementation of RoCE v2 provides
High performance computing on OCI provides powerful, cost-effective computing capabilities to solve complex mathematical and scientific problems across industries.
The chart shows the performance of Oracle’s cluster networking fabric. Below 10,000 simulation cells per core, OCI can scale above 100% with popular CFD codes, the same performance you would see on-premises. It’s important to note that without the penalty of virtualization, bare metal HPC machines can use all the cores on the node without having to reserve any cores for costly overhead.
HPC on OCI rivals the performance of on-premises solutions with the elasticity and consumption-based costs of the cloud, offering on-demand potential to scale tens of thousands of cores simultaneously. Customers get access to high-frequency processors; fast and dense local storage; high-throughput, ultralow-latency RDMA cluster networks; and the tools to automate and run jobs seamlessly.
OCI can provide latencies as low as 1.7 microseconds—lower than any other cloud vendor, according to an analysis by Exabyte.io. By enabling RDMA-connected clusters, OCI has expanded cluster networking for bare metal servers equipped with NVIDIA H100 and A100 GPUs. The groundbreaking back-end network fabric lets customers create clusters with the same low-latency networking and application scalability that can be achieved on-premises.
OCI’s bare metal NVIDIA GPU instances offer startups a high performance computing platform for applications that rely on deep learning, recommendation systems, and massively parallel high performance computing jobs. GPU instances are ideally suited for model training, inference computation, physics and image rendering, and massively parallel applications.
OCI offers instances with eight NVIDIA H100 or NVIDIA A100 GPUs. While OCI Supercluster provides the ability to scale up to hundreds or thousands of GPUs per cluster, OCI also offers the capability to deploy at a much smaller scale, starting with just a single GPU.
Customers such as Adept, an ML research and product lab developing a universal AI teammate, are using the power of OCI and NVIDIA technologies to build the next generation of AI models. Running thousands of NVIDIA GPUs on clusters of OCI bare metal compute instances and capitalizing on OCI’s network bandwidth, Adept can train large-scale AI and ML models faster and more economically than before.
“Our collaboration with Oracle and use of Oracle Cloud Infrastructure along with our Microsoft Azure AI infrastructure, will expand access to customers and improve the speed of many of our search results.”
Divya Kumar, Global Head of Marketing for Search and AI
Microsoft
“With the scalability and computing power of OCI and NVIDIA technology, we are training a neural network to use every software application, website, and API in existence—building on the capabilities that software makers have already created.”
David Luan, CEO
Adept
Learn why MosaicML found that OCI is the best foundation for AI training.
“We view this relationship with OCI as long term. We’re excited about taking advantage of the GPUs and using that to train our next generation of voice AI. There's a lot that we think that OCI will provide for us in terms of future growth.”
James Hom, Cofounder and Vice President of Products
SoundHound
“With Oracle Cloud, we’re running between four and eight GPUs in parallel to vastly accelerate our research progress, meaning we can complete an experiment in just a few hours.”
Hyeokhyen Kwon, Assistant Professor, Biomedical Informatics
Emory University
“Softdrive is the future of business computers. In the cloud PC market, performance means everything. NVIDIA GPUs on OCI bare metal servers have dramatically improved the experience for our customers.”
Leonard Ivey, Cofounder
Softdrive
Researchers used high-performance virtual machines and remote NVIDIA A100 Tensor Core GPUs, which proved effective for running the team’s memory-hungry summarization algorithms.
OCI provides world-class technical experts to help you get up and running. We remove the technical barriers of a complex deployment—from planning to launch—to help ensure your success.
OCI is built for enterprises seeking higher performance, consistently lower costs, and easier cloud migration for their current on-premises applications.
Sagar Rawal, Vice President, Oracle Cloud Infrastructure
Today at SC23, we’re announcing our upcoming plans to offer Oracle Cloud Infrastructure (OCI) Compute instances powered by the NVIDIA GH200 Grace Hopper Superchip. The GH200 consists of an Arm CPU (Grace) linked to an NVIDIA H100 Tensor Core GPU (Hopper) with a high-bandwidth memory space of 576 GB.
Read the complete post