Enterprise-class co-designed software and hardware solutions from HPE and NVIDIA accelerate development and deployment of GenAI applications

Today at NVIDIA GTC, Hewlett Packard Enterprise (NYSE: HPE) announced updates to one of the industry’s most comprehensive AI-native portfolios to advance the operationalization of generative AI (GenAI), deep learning, and machine learning (ML) applications. The updates include:

• Availability of two HPE and NVIDIA co-engineered full-stack GenAI solutions.
• A preview of HPE Machine Learning Inference Software.
• An enterprise retrieval-augmented generation (RAG) reference architecture.
• Support to develop future products based on the new NVIDIA Blackwell platform.

“To deliver on the promise of GenAI and effectively address the full AI lifecycle, solutions must be hybrid by design,” said Antonio Neri, president and CEO at HPE. “From training and tuning models on-premises, in a colocation facility or the public cloud, to inferencing at the edge, AI is a hybrid cloud workload. HPE and NVIDIA have a long history of collaborative innovation, and we will continue to deliver co-designed AI software and hardware solutions that help our customers accelerate the development and deployment of GenAI from concept into production.”

“Generative AI can turn data from connected devices, data centers and clouds into insights that can drive breakthroughs across industries," said Jensen Huang, founder and CEO at NVIDIA. "Our growing collaboration with HPE will enable enterprises to deliver unprecedented productivity by leveraging their data to develop and deploy new AI applications to transform their businesses.”

Supercomputing-powered GenAI training and tuning

Announced at SC23, HPE’s supercomputing solution for generative AI is now available to order for organizations seeking a preconfigured and pretested full-stack solution for the development and training of large AI models. Purpose-built to help customers accelerate GenAI and deep learning projects, the turnkey solution is powered by NVIDIA and can support up to 168 NVIDIA GH200 Grace Hopper Superchips.

The solution enables large enterprises, research institutions, and government entities to streamline the model development process with an AI/ML software stack that helps customers accelerate GenAI and deep learning projects, including LLMs, recommender systems, and vector databases. Delivered with services for installation and set-up, this turnkey solution is designed for use in AI research centers and large enterprises to realize improved time-to-value and speed up training by 2-3X. For more information or to order it today, visit HPE's supercomputing solution for generative AI.

Enterprise-class GenAI tuning and inference

Previewed at Discover Barcelona 2023, HPE’s enterprise computing solution for generative AI is now available to customers directly or through HPE GreenLake with a flexible and scalable pay-per-use model. Co-engineered with NVIDIA, the pre-configured fine-tuning and inference solution is designed to reduce ramp-up time and costs by offering the right compute, storage, software, networking, and consulting services that organizations need to produce GenAI applications. The AI-native full-stack solution gives businesses the speed, scale and control necessary to tailor foundational models using private data and deploy GenAI applications within a hybrid cloud model.

Featuring a high-performance AI compute cluster and software from HPE and NVIDIA, the solution is ideal for lightweight fine-tuning of models, RAG, and scale-out inference. The fine-tuning time for a 70 billion parameter Llama 2 model running this solution decreases linearly with node count, taking six minutes on a 16-node system¹. The speed and performance enable customers to realize faster time-to-value by improving business productivity with AI applications like virtual assistants, intelligent chatbots, and enterprise search.

Powered by HPE ProLiant DL380a Gen11 servers, the solution is pre-configured with NVIDIA GPUs, the NVIDIA Spectrum-X Ethernet networking platform, and NVIDIA BlueField-3 DPUs. The solution is enhanced by HPE’s machine learning platform and analytics software, NVIDIA AI Enterprise 5.0 software with new NVIDIA NIM microservice for optimized inference of generative AI models, as well as NVIDIA NeMo Retriever and other data science and AI libraries.

To address the AI skills gap, HPE Services experts will help enterprises design, deploy, and manage the solution, which includes applying appropriate model tuning techniques. For more information or to order it today, visit HPE’s enterprise computing solution for generative AI.

From prototype to productivity

HPE and NVIDIA are collaborating on software solutions that will help enterprises take the next step by turning AI and ML proofs-of-concept into production applications. Available to HPE customers as a technology preview, HPE Machine Learning Inference Software will allow enterprises to rapidly and securely deploy ML models at scale. The new offering will integrate with NVIDIA NIM to deliver NVIDIA-optimized foundation models using pre-built containers.

To assist enterprises that need to rapidly build and deploy GenAI applications that feature private data, HPE developed a reference architecture for enterprise RAG, available today, that is based on the NVIDIA NeMo Retriever microservice architecture. The offering consists of a comprehensive data foundation from HPE Ezmeral Data Fabric Software and HPE GreenLake for File Storage. The new reference architecture will offer businesses a blueprint to create customized chatbots, generators, or copilots.

To aid in data preparation, AI training, and inferencing, the solution merges the full spectrum of open-source tools and solutions from HPE Ezmeral Unified Analytics Software and HPE’s AI software, which includes HPE Machine Learning Data Management Software, HPE Machine Learning Development Environment Software, and the new HPE Machine Learning Inference Software. HPE’s AI software is available on both HPE’s supercomputing and enterprise computing solutions for generative AI to provide a consistent environment for customers to manage their GenAI workloads.

Next-gen solutions built on NVIDIA Blackwell platform

HPE will develop future products based on the newly announced NVIDIA Blackwell platform, which incorporates a second-generation Transformer Engine to accelerate GenAI workloads. Additional details and availability for forthcoming HPE products featuring the NVIDIA GB200 Grace Blackwell Superchip, the HGX B200, and the HGXB100 will be announced in the future.

About Hewlett Packard Enterprise

Hewlett Packard Enterprise (NYSE: HPE) is the global edge-to-cloud company that helps organizations accelerate outcomes by unlocking value from all of their data, everywhere. Built on decades of reimagining the future and innovating to advance the way people live and work, HPE delivers unique, open, and intelligent technology solutions as a service. With offerings spanning Cloud Services, Compute, High Performance Computing & AI, Intelligent Edge, Software, and Storage, HPE provides a consistent experience across all clouds and edges, helping customers develop new business models, engage in new ways, and increase operational performance. For more information, visit: www.hpe.com

¹ Based on initial internal benchmarks of llama-recipes finetuning.py that tracked the average epoch time to fine-tune eight nodes at 594 seconds and 16 nodes at 369 seconds with flash attention and parameter efficient fine-tuning.

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