Dell EMC Integrated System for Microsoft Azure Stack Hub has been extending Microsoft Azure services to customer-owned data centers for over three years. Our platform has enabled organizations to create a hybrid cloud ecosystem that drives application modernization and to address business concerns around data sovereignty and regulatory compliance. 

Dell Technologies, in collaboration with Microsoft, is excited to announce upcoming enhancements that will unlock valuable, real-time insights from local data using GPU-accelerated AI and ML capabilities. Actionable information can be derived from large on-premises data sets at the intelligent edge without sacrificing security. 

Partnership with NVIDIA

Today, customers can order our Azure Stack Hub dense scale unit configuration with NVIDIA Tesla V100S GPUs for running compute-intensive AI processes like inferencing, training, and visualization from virtual machine or container-based applications. Some customers choose to run Kubernetes clusters on their hardware-accelerated Azure Stack Hub scale units to process and analyze data sent from IoT devices or Azure Stack Edge appliances. Powered by the Dell EMC PowerEdge R840 rack server, these NVIDIA Tesla V100S GPUs use Discrete Device Assignment (DDA), also known as GPU pass-through, to dedicate one or more GPUs to an Azure Stack Hub NCv3 VM. 

The following figure illustrates the resources installed in each GPU-equipped Azure Stack Hub dense configuration scale unit node. 

This month, our Dell EMC Azure Stack Hub release 2011 will also support the NVIDIA T4 GPU – a single-slot, low-profile adapter powered by NVIDIA Turing Tensor Cores.   These GPUs are perfect for accelerating diverse cloud-based workloads, including light machine learning, inference, and visualization. These adapters can be ordered with Dell EMC Azure Stack Hub all-flash scale units powered by Dell EMC PowerEdge R640 rack servers. Like the NVIDIA Tesla V100S, these GPUs use DDA to dedicate one adapter’s powerful capabilities to a single Azure Stack Hub NCas_v4 VM. A future Azure Stack Hub release will also enable GPU partitioning on the NVIDIA T4.

The following figure illustrates the resources installed in each GPU-equipped Azure Stack Hub all-flash configuration scale unit node. 

Partnership with AMD

We are also pleased to announce a partnership with AMD to deliver GPU capabilities in our Dell EMC Integrated System for Microsoft Azure Stack Hub. Available today, customers can order our dense scale unit configuration with AMD Radeon Instinct MI25 GPUs aimed at graphics intensive visualization workloads like simulation, CAD applications, and gaming. The MI25 uses GPU partitioning (GPU-P) technology to allow users of an Azure Stack Hub NVv4 VM to consume only a portion of the GPU’s resources based on their workload requirements. 

The following table is a summary of our hardware acceleration capabilities. 

An engineered approach

Following our stringent engineered approach, Dell Technologies goes far beyond considering GPUs as just additional hardware components in the Dell EMC Integrated System for Microsoft Azure Stack Hub portfolio. We apply our pedigree as leaders in appliance-based solutions to the entire lifecycle of all our scale unit configurations. The dense and all-flash scale unit configurations with integrated GPUs are designed to follow best practices and use cases specifically with Azure-based workloads, rather than workloads running on traditional virtualization platforms. Dell Technologies is also committed to ensuring a simplified experience for initial deployment, patch and update, support, and streamlined operations and monitoring for these new configurations.

Additional considerations

There are a couple of additional details worth mentioning about our new Azure Stack Hub dense and all-flash scale unit configurations with hardware acceleration:

• The use of the GPU-backed N-Series VMs in Azure Stack Hub for compute-intensive AI and ML workloads is still in preview. Dell Technologies is very interested in speaking with customers about their use cases and workloads supported by this configuration. Please contact us at mhc.preview@dell.com to speak with one of our engineering technologists.  
• The Dell EMC Integrated System for Microsoft Azure Stack Hub configurations with GPUs can be delivered fully racked and cabled in our Dell EMC rack. Customers can also elect to have the scale unit components re-racked and cabled in their own existing cabinets with the assistance of Dell Technologies Services.

Resources for further study

• At the time of publishing this blog post, only the NCv3 and NVv4 VMs are available in the Azure Stack Hub marketplace. The NCas_v4 currently is not visible in the portal. Please proceed to the Azure Stack Hub User Documentation for more information on these VM sizes.
• Customers may want to explore the Train Machine Learning (ML) model at the edge design pattern in the Azure Hybrid Documentation. This may prove to be a good starting point for putting this technology to work for their organization.
• Customers considering running AI and ML workloads on Dell EMC Integrated System for Microsoft Azure Stack Hub can also greatly benefit from storage-as-a-service with Dell EMC PowerScale. PowerScale can help enable faster training and validation of AI models, improve model accuracy, drive higher GPU utilization, and increase data science productivity. Visit Artificial Intelligence with Dell EMC PowerScale for more information.