Enterprises are looking for increasingly powerful compute to support their AI workloads and accelerate data processing. The efficiency gained can translate to better returns for their investments in AI training and fine-tuning, and improved user experiences for AI inference.
At the Oracle CloudWorld conference today, Oracle Cloud Infrastructure (OCI) announced the first zettascale OCI Supercluster, accelerated by the NVIDIA Blackwell platform, to help enterprises train and deploy next-generation AI models using more than 100,000 of NVIDIA's latest-generation GPUs.
OCI Superclusters allow customers to choose from a wide range of NVIDIA GPUs and deploy them anywhere: on premises, public cloud and sovereign cloud. Set for availability in the first half of next year, the Blackwell-based systems can scale up to 131,072 Blackwell GPUs with NVIDIA ConnectX-7 NICs for RoCEv2 or NVIDIA Quantum-2 InfiniBand networking to deliver an astounding 2.4 zettaflops of peak AI compute to the cloud. (Read the press release to learn more about OCI Superclusters.)
At the show, Oracle also previewed NVIDIA GB200 NVL72 liquid-cooled bare-metal instances to help power generative AI applications. The instances are capable of large-scale training with Quantum-2 InfiniBand and real-time inference of trillion-parameter models within the expanded 72-GPU NVIDIA NVLink domain, which can act as a single, massive GPU.
This year, OCI will offer NVIDIA HGX H200 - connecting eight NVIDIA H200 Tensor Core GPUs in a single bare-metal instance via NVLink and NVLink Switch, and scaling to 65,536 H200 GPUs with NVIDIA ConnectX-7 NICs over RoCEv2 cluster networking. The instance is available to order for customers looking to deliver real-time inference at scale and accelerate their training workloads. (Read a blog on OCI Superclusters with NVIDIA B200, GB200 and H200 GPUs.)
OCI also announced general availability of NVIDIA L40S GPU-accelerated instances for midrange AI workloads, NVIDIA Omniverse and visualization. (Read a blog on OCI Superclusters with NVIDIA L40S GPUs.)
For single-node to multi-rack solutions, Oracle's edge offerings provide scalable AI at the edge accelerated by NVIDIA GPUs, even in disconnected and remote locations. For example, smaller-scale deployments with Oracle's Roving Edge Device v2 will now support up to three NVIDIA L4 Tensor Core GPUs.
Companies are using NVIDIA-powered OCI Superclusters to drive AI innovation. Foundation model startup Reka, for example, is using the clusters to develop advanced multimodal AI models to develop enterprise agents.
Reka's multimodal AI models, built with OCI and NVIDIA technology, empower next-generation enterprise agents that can read, see, hear and speak to make sense of our complex world, said Dani Yogatama, cofounder and CEO of Reka. With NVIDIA GPU-accelerated infrastructure, we can handle very large models and extensive contexts with ease, all while enabling dense and sparse training to scale efficiently at cluster levels.
NVIDIA received the 2024 Oracle Technology Solution Partner Award in Innovation for its full-stack approach to innovation.
Accelerating Generative AI Oracle Database Workloads Oracle Autonomous Database is gaining NVIDIA GPU support for Oracle Machine Learning notebooks to allow customers to accelerate their data processing workloads on Oracle Autonomous Database.
At Oracle CloudWorld, NVIDIA and Oracle are partnering to demonstrate three capabilities that show how the NVIDIA accelerated computing platform could be used today or in the future to accelerate key components of generative AI retrieval-augmented generation pipelines.
The first will showcase how NVIDIA GPUs can be used to accelerate bulk vector embeddings directly from within Oracle Autonomous Database Serverless to efficiently bring enterprise data closer to AI. These vectors can be searched using Oracle Database 23ai's AI Vector Search.
The second demonstration will showcase a proof-of-concept prototype that uses NVIDIA GPUs, NVIDIA cuVS and an Oracle-developed offload framework to accelerate vector graph index generation, which significantly reduces the time needed to build indexes for efficient vector searches.
The third demonstration illustrates how NVIDIA NIM, a set of easy-to-use inference microservices, can boost generative AI performance for text generation and translation use cases across a range of model sizes and concurrency levels.
Together, these new Oracle Database capabilities and demonstrations highlight how NVIDIA GPUs can be used to help enterprises bring generative AI to their structured and unstructured data housed in or managed by an Oracle Database.
Sovereign AI Worldwide NVIDIA and Oracle are collaborating to deliver sovereign AI infrastructure worldwide, helping address the data residency needs of governments and enterprises.
Brazil-based startup Wide Labs trained and deployed Amazonia IA, one of the first large language models for Brazilian Portuguese, using NVIDIA H100 Tensor Core GPUs and the NVIDIA NeMo framework in OCI's Brazilian data centers to help ensure data sovereignty.
Developing a sovereign LLM allows us to offer clients a service that processes their data within Brazilian borders, giving Amaz nia a unique market position, said Nelson Leoni, CEO of Wide Labs. Using the NVIDIA NeMo framework, we successfully trained Amaz nia IA.
In Japan, Nomura Research Institute, a leading global provider of consulting services and system solutions, is using OCI's Alloy infrastructure with NVIDIA GPUs to enhance its financial AI platform with LLMs operating in accordance with financial regulations and data sovereignty requirements.
Communication and collaboration company Zoom will be using NVIDIA GPUs in OCI's Saudi Arabian data centers to help support compliance with local data requirements.
And geospat
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Enterprises are looking for increasingly powerful compute to support their AI workloads and accelerate data processing. The efficiency gained can translate to better returns for their investments in AI training and fine-tuning, and improved user experiences for AI inference.
