At a virtual multi-cloud event VMworld 2021, NVIDIA announced that it is extending its partnership with Lenovo to include participation in NVIDIA’s early access programme in support of Project Monterey – which is designed to modernise enterprise data centres with security and performance of NVIDIA Bluefield data processing units.
With this, NVIDIA, Lenovo and VMware are collaborating to transform the data centre, cloud and edge architecture to be software-defined and hardware-accelerated for tackling modern workloads.
You can register for NVIDIA’s early access programme here.
Besides this, VMware, alongside NVIDIA, also announced an upcoming update to VMware vSphere with Tanzu, a virtualisation platform for IT teams to get started with Kubernetes workloads on existing infrastructure. With this, the duo looks to develop an AI-ready enterprise platform that brings the world’s leading AI stack and optimised software to the infrastructure used by enterprises worldwide.
Enabling Secure, Accelerated Data Centers
A year ago – at the VMworld 2020 – Project Monterey was announced by VMware in collaboration with NVIDIA and other ecosystem partners. The initiative aims to provide enterprise data centres performance, manageability, and security via NVIDIA BlueField DPUs. BlueField DPUs – which is built for AI and accelerated computing – enables the delivery of applications at any scale by offloading, accelerating and isolating data centres workloads.
The Project Monterey latest announcement comes at a time when AI and machine learning are transforming data centres, driving demand for new architectures and workloads. NVIDIA’s early access programme allows enterprises to venture into VMware-enabled pre-configured clusters accelerated by BlueField-enabled servers. It includes Lenovo ThinkAgile VX and ThinkSystem Ready-Nodes.
Justin Boitano, VP and GM of enterprise and edge computing at NVIDIA, said that Project Monterey early access programme is a key step in allowing enterprises to embrace AI’s transformational benefits while tackling security and performance challenges.
Kamran Amini, VP and GM of server, storage and software-defined solutions at Lenovo ISG, said this programme enables a fundamental solution shift towards advanced, DPU-powered data centre architecture. “NVIDIA BlueField DPUs provide performance and security, which enhance the modern data centre that is software-defined and hardware accelerated,” he added.
Delivering AI at Scale for the Enterprise
With the latest update to VMware vSphere with Tanzu, enterprises can now run trials of their AI projects in conjunction with the NVIDIA AI Enterprise software suite. Launched in August 2021, NVIDIA AI Enterprise is an end-to-end, cloud-native suite of artificial intelligence and data analytics frameworks and tools optimised, certified and supported by NVIDIA to enable rapid deployment, management and scaling of AI/ML applications in the modern hybrid cloud.
Simplifying AI Workloads
Bridging the void between the worlds of IT operations, data scientists and application developers, NVIDIA AI Enterprise has simplified the AI development lifecycle to help customers get projects into production faster. In addition, NVIDIA AI Enterprise and VMware vSphere with Tanzu enables developers to run AI workloads on Kubernetes containers within their VMware environments, leveraging infrastructure managed by IT.
The software runs on mainstream, NVIDIA-Certified Systems from leading server manufacturers, where it provides an integrated, complete stack of software and hardware optimised for AI.
Lee Caswell, vice president of marketing for the cloud infrastructure business group at VMware, said their collaboration with NVIDIA enables customers to develop and deploy advanced AI applications on their hybrid clouds.
Enterprise-Grade AI for Developers
NVIDIA AI Enterprise offers AI software such as PyTorch, TensorFlow, NVIDIA TensorRT, NVIDIA Triton Inference Server and NVIDIA RAPIDS. Thus, making it easier for AI developers and data scientists to access tools and frameworks needed to build a host of enterprise AI applications such as conversational AI, computer vision, and recommendation systems.
Moreover, it enables IT to manage all clusters and apps across their hybrid cloud infrastructure. Even in virtual environments, NVIDIA AI Enterprise delivers near-bare-metal AI performance so that IT teams can help developers rapidly explore ideas and iterate as they build their models.
NVIDIA Partner Ecosystem
NVIDIA AI Enterprise is supported by a broad range of server manufacturers offering NVIDIA-Certified Systems. Some of them include Dell Technologies, GIGABYTE, H3C, Hewlett Packard Enterprise, Inspur, Lenovo, and Supermicro – all of which feature NVIDIA GPUs like the NVIDIA A30 and NVIDIA A100.
The software is also available worldwide from NVIDIA channel partners, including Atea, Axians, Carahsoft Technology Corp., Computacenter, Insight Enterprises, NTT, Presidio, Sirius, SoftServe, SVA System Vertrieb Alexander GmbH, TD SYNNEX, Trace3, and WWT.
One of the early adopters, Dell Technologies, submitted MLPerf benchmark achievement of 94.4 per cent to 100 per cent of the equivalent bare-metal performance running NVIDIA AI Enterprise and VMware vSphere with three NVIDIA A100 Tensor Core GPUs in a Dell EMC PowerEdge R7525 server.
John Fanelli, vice president of Enterprise Product Management at NVIDIA, said that the submission is the second time a vendor has submitted MLPerf results on virtualised infrastructure. “This reflects how NVIDIA AI Enterprise is designed to power advanced AI workloads on accelerated industry-standard centre servers in the modern data centre,” he added.
Further, to support customers needing instant access to AI infrastructure, NVIDIA AI Enterprise is also expected to launch the NVIDIA AI LaunchPad programme available with Equinix, a leading digital infrastructure company.
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Amit Raja Naik is a senior writer at Analytics India Magazine, where he dives deep into the latest technology innovations. He is also a professional bass player.