NVIDIA AI Enterprise is an end-to-end, cloud-native suite of AI and data analytics software optimized, certified, and supported by NVIDIA to run on VMware vSphere with NVIDIA-Certified Systems™. It includes key NVIDIA technologies for rapidly deploying, managing and scaling AI workloads in the modern hybrid cloud.
VMWARE + NVIDIA KI-ENABLED PLATFORM
MEET THE NVIDIA EGX PLATFORM
One architecture. For every enterprise workload. Discover the platform that unifies the data center and
brings accelerated computing to every enterprise.
MORE INFOADVANTAGES
OPTIMIZED FOR PERFORMANCE
Achieve near bare-metal performance across multiple nodes to enable large, complex training and machine learning workloads.
CERTIFIED FOR RED HAT AND VMWARE VSPHERE
Reduce deployment risk with a full suite of NVIDIA AI software certified for the VMware and Red Hat data center.
NVIDIA ENTERPRISE SUPPORT
Ensure mission-critical AI projects stay on track with enterprise-level support from NVIDIA.
FLEXIBILITY THROUGH RED HAT OPENSHIFT
Diese gemeinsame Lösung von NVIDIA und Red Hats gibt Datenwissenschaftlern die Flexibilität, ML-Tools in Containern zu verwenden, um ihre ML-Modellierungsergebnisse schnell zu erstellen, zu skalieren, zu reproduzieren und zu teilen.
KI READY FOR ANY WORKLOAD
Unterstützung für Deep Learning-Frameworks und Data Science-Container auf reinen CPU-Systemen. Jetzt können Unternehmen KI auf GPU-beschleunigten NVIDIA-zertifizierten Servern oder auf denselben Servermodellen ohne GPUs ausführen. So können Sie KI auf einer bestehenden Infrastruktur einsetzen und sich dabei von den NVIDIA KI-Experten unterstützen lassen.
SUPPORT FOR NEW NVIDIA HARDWARE
Support for new NVIDIA hardware, including the NVIDIA A100X and A30X converged accelerators that enable faster, more efficient, and more secure AI systems, and the NVIDIA A2 GPU for space-constrained environments.
NEW UPDATED NVIDIA AI CONTAINERS
NVIDIA TAO Toolkit and the updated Triton Inference Server with FIL, further streamline AI development and deployment. The NVIDIA TAO Toolkit accelerates AI development by 10x without requiring AI expertise. The updated NVIDIA Triton Inference Server now supports a FIL (Forest Inference Library) backend that provides the best inference performance for both neural networks and tree-based models on GPUs, enabling simplified deployment of large tree models on GPUs with low latency and high accuracy. Examples of the use of tree-based models include fraud detection, sales forecasting, product defect prediction, pricing, recommender systems, and call center routing, to name a few.
DEPLOYMENT OF KI IN THE CLOUD
Support for NVIDIA AI Enterprise based Virtual Machine Images (VMIs) for use in Cloud Service Provider (CSP) infrastructure. Customers who have purchased NVIDIA AI Enterprise software can now deploy to specific NVIDIA GPU-accelerated cloud instances in AWS, Azure, or GCP instances with full support from NVIDIA.
TerminologyNOTICE | MEANING |
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Support Services | Includes technical support, upgrade and maintenance. |
Unlimited license | A non-expiring, permanent software license that can be used in perpetuity without the need to renew. Support Services are required and are available in three- or five-year increments. One-year support services are available for renewals only. |
Subscription | A software license that is active for a specified period of time defined by the terms of the subscription. A subscription includes support services for the duration of the subscription term. |
License server | An application that manages licensing and is installed on a physical or virtual server. |
GPU | Graphics processing unit |
CPU | The central processing unit (CPU) of a computer is the part of the computer that retrieves and executes instructions. |
CPU socket licensing | (1) For on-premise deployments, the number of physical processors in the computing environment on which NVIDIA AI Enterprise is installed, or (2) in a cloud computing environment, the number of virtual CPUs for the computing instance on which NVIDIA AI Enterprise is running. NVIDIA requires one license per CPU socket. |
NVIDIA Virtual GPU Software Licensed ProductsPRODUCT | DESCRIPTION |
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Virtuelle NVIDIA-Anwendungen (vApps)l | For organizations using Citrix virtual apps and desktops, RDSH or other app streaming or session-based solutions. Designed for PC-level applications and server-based desktops. |
NVIDIA Virtueller PC (vPC) | For users who want a virtual desktop but want a great PC Windows applications, browsers and high-definition high-definition video. |
NVIDIA RTX™ Virtual Workstation (vWS) | For users who want to be able to run professional remote graphics applications with full performance on any device, anywhere |
NVIDIA Virtual Compute Server (vCS) | For compute-intensive server workloads, such as artificial intelligence (AI), deep learning, or high-performance computing (HPC). |
Supported NVIDIA GPUs optimized for compute loads | NVIDIA HGX A100 | NVIDIA A100 | NVIDIA A30 |
---|
Recommended use case | Optimized calculations | Optimized calculations | Optimized calculations |
Number of GPUs | 4 NVIDIA A100/ 8 NVIDIA A100 | 1 NVIDIA A100
| 1 NVIDIA A100
|
FP32 Cores / GPU | 6,912 | 6,912 | 3584 |
Tensor-Cores / GPU RT-Cores | 432 | 432 | 224 |
RT-Cores | - | - | - |
Total memory size / GPU | 40 GB HBM2/80GB HBM2 | 40 GB HBM2/80GB HBM2 | 24 GB HBM2 |
MIG-Instanzen/GPU | 7
| 7 | 4 |
Max GPU Power / GPU | 400 W | 250W/300W | 165 W |
Form factor | 4x SXM4 GPUs/8x SXM4
| PCIe 4.0 Dual-Slot FHFL | PCIe 4.0 Dual-Slot FHFL |
Card dimensions | - | 10.5” × 4.4”
| 10.5” × 4.4”
|
Cooling solution | Passive | Passive | Passive |
Our products | HGX A100 - SERVER SYSTEMS | A100 - SERVER SYSTEMS | NVIDIA A30 GPU |
Supported NVIDIA GPUs optimized for mixed workloads | NVIDIA HGX 100 | NVIDIA A10 | NVIDIA T4 |
---|
Recommended use case | Optimized calculations | NVIDIA vWS – Performance Optimized (midrange) vCS – Compute Optimized | NVIDIA vWS - Performance Optimized (Entry); vPC - Density Optimized; vCS – Compute Optimized |
Number of GPUs | 4 NVIDIA A100/ 8 NVIDIA A100 | 1 NVIDIA A10 | 1 NVIDIA Turing ™ TU104 |
FP32 Cores / GPU | 6,912 | 9,216 | 2,560 |
Tensor-Cores / GPU RT-Cores | 432 | 288 | 320 |
RT-Cores | - | 72 | 40
|
Total memory size / GPU | 40 GB HBM2/80GB HBM2 | 24 GB GDDR6 | 16 GB GDDR6 |
Max GPU Power / GPU | 400 W | 150 W | 70 W |
Form factor | 4x SXM4 GPUs/8x SXM4
| PCIe 4.0 Single Slot FHFL | PCIe 3.0 Single Slot |
Card dimensions | - | 10.5” × 4.4” | 2.7" × 6.6" |
Cooling solution | Passive | Passive | Passive |
Our products | HGX A100 - SERVER SYSTEMS | NVIDIA A10 GPU | NVIDIA T4 GPU |
General information on procurementELIGIBILITY | NVIDIA vGPU PRODUCTION SUMS |
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Maintenance | Access to all maintenance releases, bug fixes, and security security patches for flexible upgrades in accordance with the NVIDIA Virtual GPU Software Lifecycle Policy. |
Upgrades | Access to all new major versions with feature enhancements. Enhancements and new hardware support |
Long-term maintenance of branch offices | Available for up to 3 years from general availability per the NVIDIA Virtual GPU Software Lifecycle Policy |
Direct support | Direct access to NVIDIA support for timely resolution of of customer specific issues |
Support availability | Customer support available during normal business hours Cases 24 × 7 accepted |
Access to the knowledgebase | ✓
|
Web support | ✓ |
E-Mail support | ✓ |
Phone support | ✓ |
SPEED UP YOUR KI JOURNEY WITH NVIDIA LAUNCHPAD
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with Triton Inference Server to image classification with TensorFlow and much more.