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Radeon Instinct Accelerators

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With all the excitement around the general availability of Microsoft’s Azure NVv4 instances, I wanted to reshare this MxGPU white paper that AMD’s Tonny Wong created when we first launched the SR-IOV based GPU virtualization architecture. This is a great paper for anyone wanting to understand and learn more about the underlining technology within our GPU architecture.  (Note: we have made a few updates to the paper below to keep it current.)

 

White Paper - AMD MULTIUSER GPU

Originally created by Tonny Wong, Radeon Technologies Group

 

 

SR-IOV-BASED GPU VIRTUALIZATION FOR A TRUE WORKSTATION EXPERIENCE

 

 

Overview

Virtual Desktop Infrastructure (VDI) has evolved over the last few years, enabling richer user experiences and improved manageability and deployment ease. Many traditional VDI enterprise customers have gained productivity and lowered Total Cost of Ownership (TCO) for their desktop users. The growth of VDI needs to address the needs of “greenfield” users, those organizations that want the benefits of secure hosted desktops but with a deployment model that is more consistent with their traditional desk-side workstations. These deployments need to abide to existing datacenter standards for hypervisors while leveraging capabilities that match traditional workstations.

 

The Trend Toward VDI

Remote graphics protocols have greatly improved user experiences, delivering the feel of a local workstation computing resource for LAN users and optimizing multimedia and graphics capabilities for WAN users. These remote protocols can deliver GPU-rendered content from the datacenter allowing Virtual Machines with standard desktop OS’s to be the main deployment method for users of all types. From demanding workstation applications with high 3D GPU needs all the way to standard enterprise desktop users who want GPU-enriched desktop experiences, this range of users can take advantage of a vast array of VDI solutions now in the market.

 

VDI is a great way to help improve desktop security by hosting out of an enterprise private cloud (on-premise datacenter) or via offerings from cloud service providers either fully public or via hybrid public/private clouds.  However, the capabilities should match what users expect from their local workstation systems and not be limited to a subset of features. Enterprise VDI deployments should have access to GPU resources in the datacenter or service provider that deliver 3D capabilities across many users while still making all graphics API and compute API standards are available, just like on local workstation systems.

 

What AMD GPUs bring to the Virtual Desktop GPU technology for VDI allows users migrating from physical workstation desktop systems or notebooks to capture the same or better graphics capabilities as their desktop workstation, with good productivity while enabling more user types to migrate to VDI. In supporting this migration to VDI, GPU vendors need to ensure that, when enabling a GPU for virtualization across many users, this GPU must deliver deterministic performance, helping to better gauge user types and numbers of GPU resources needed.

 

AMD has spent the last few years implementing features in our GPU hardware to prepare for virtualized platforms.  Implementation in our silicon allows our new AMD Multiuser GPU technology to share the GPU resource across multiple users or virtual machines while giving the expanded capabilities users expect from local workstations utilizing discrete GPUs. The AMD Multiuser GPU products can provide enterprise customers with a choice for their GPU and 3D processing needs that can help make GPU use more pervasive on VDI deployments.

 

VDI with GPUs: Lifting Performance and User Experience

With Virtual Desktop Infrastructure (VDI), one can gain the benefits of security, manageability, and remote access to deploy and support enterprise desktop users and may additionally experience lower total cost of ownership (TCO). For the knowledge worker and task worker user types, VDI deployments help apply better control of user environments while enabling increased performance by virtue of virtual machines being closer to datacenter, hosted datasets or applications.

 

Users who required higher computing power specifically around GPU technology for 3D and GPU compute applications were either left on physical desktop systems or deployed with comparatively expensive pass through GPU technology, losing the benefit of distributing the graphics card cost among multiple users.  Early virtualized GPU technologies addressed some of these areas by adapting a standard GPU architecture to virtualization via software in the hypervisor, but this isn’t the ideal solution to mimic true discrete GPU-like performance. Features like GPU compute functionality are not available, limiting some applications to fallback to CPU usage when a desktop workstation would have leveraged a GPU.  Initial pricing for these virtualized GPU solutions was compelling compared to multiple pass-thru GPU devices but they can still have much greater costs than multiple desktop discrete GPUs. Standard VDI technologies utilize software-emulated GPUs, specifically in VMware vSphere with Horizon View, where the base level graphics capabilities are limited.  This works fine for knowledge workers where enabling software 3D emulation with Virtual Shared Graphics Acceleration (vSGA) allows basic applications to run, albeit with higher CPU utilization. vSGA performance is further enhanced by leveraging a hardware GPU with appropriate vSGA drivers from graphics vendors. Even with hardware vSGA support, however, it does not necessarily meet the requirements for more intensive 3D Graphics and Compute user needs. Certifications (CAD/CAE as an example) for applications are not available due to limited support level in graphics APIs like OpenGL® or DirectX®.

 

Virtualized GPUs allow workstation and power user categories to migrate to VDI with acceptable GPU performance. Workstation users from CAD/CAE, M&E and specialized segments can leverage workstation-class drivers on applicable platforms to support applications with certification requirements.  Power users who rely on DTP/Desktop Publishing, or internal enterprise applications who need GPU support can migrate to VDI environments.

 

AMD Multiuser GPU – Technology Foundation

Rather than repurposing an existing GPU and adding a software layer to accommodate virtualization requirements, AMD’s Multiuser GPU approach is to create an entirely new class of GPU architecture with virtualization capabilities built into the silicon. AMD challenged the notion that the support of GPU virtualization required a proprietary software solution. Compliant with the well-established PCIE® virtualization standard SR-IOV (Single Root I/O Virtualization) specification, AMD has implemented a hardware-based GPU architecture. The culmination of these efforts resulted in the creation of the industry’s first hardware virtualized GPU. 

 

The SR-IOV specification defines a virtualized PCIE device to expose one or more physical functions

(PF) plus a number of virtual functions (VFs) on the PCIE bus. The specification also defines a standard method to enable the virtual functions by the system software such as the hypervisor or its delegate. These VFs may inherit the same graphics capabilities of the physical GPU, allowing each to become fully capable of supporting the GPU’s graphics functionality. Through the PF, system software controls enablement and access permissions of the VFs, internally mapping resources such as the graphics cores and GPU local memory.

 

The task of GPU virtualization management can therefore leverage the existing standard PCIE device management logic in the hypervisor, unburdening the hypervisor from proprietary and complex software implementations. To further simplify the deployment, an optional driver can be loaded to help the hypervisor to enable/disable virtual functions and to manage the Multiuser GPU’s resources.

 

The PF manages sharing of graphical resources by scheduling the GPU cores across VFs and allocating graphics memory to each of these VFs. The PF also assigns internal register spaces to each VF ensuring an orderly and structured method for the VFs to access hardware resources and data, at the same time helping keep that data secure. Because each GPU VF is designed to inherit the attributes of the physical GPU, it supports full GPU capabilities allowing the support of graphics and compute features.

 

When these VFs are passed through to their assigned virtual machines, they will appear as full-featured graphical devices to the virtual machine’s guest OS. Since the guest OS sees the VFs as a native graphics device, AMD’s native Radeon™ Pro™ graphics driver that are designed for professional graphics devices can be loaded within the virtual machine to unlock the GPU’s graphics and compute capabilities.

 

A number of Radeon Pro graphics products already support passthrough mode, allowing remote users the ability to access a GPU installed on a host server from a client device. AMD Multiuser GPUs evolved this architecture to support from 1 to 16 VFs, allowing each to appear as a passthrough device with added security and quality of service. Mapping one VF to a virtual machine allows the creation of up to 16 independent guest OSs that are accelerated by a single GPU. User density is limited only by the availability of PCIE slots.

 

 

Key Benefits

 

Predictable Performance

A key benefit of hardware-based virtualization is that hardware-controlled scheduling cycles deliver predictable quality of service (QoS). The fixed scheduling cycles apportioned to each VF ensure that each VF receives its fair share of GPU services.

  

Predictable performance or deterministic QoS results in smooth transitions from proof-of-concept pilots to organization-wide deployments. Pilot managers determine the capabilities of the GPU during the proof-of-concept phase and scale up or scale down user density (number of users per GPU) as required. 

Being able to determine the GPU needs of the user base ties back to an organization’s ability to forecast and plan its resources. Under-forecasting results in failing to meet users’ performance expectations; over-forecasting results in under-utilizing a configuration. The predictable nature of AMD’s Multiuser GPU solution helps avoid these unwanted outcomes.

 

 

Secure Implementation

The push towards virtualization is in part driven by the needs of centralizing and securing data and resources. The cornerstone of AMD’s Multiuser GPU technology is its ability to preserve the data integrity of virtualized desktops and their application data. The hardware-enforced memory isolation logic provides strong data security among the VFs, which helps prevent one VM from being able to access another VM’s data.

  

With security being a bare minimum requirement for any virtualization solution, AMD’s hardware-based virtualized GPU solution offers a strong deterrent to unauthorized users who traverse the software or application layers seeking means to extract or corrupt GPU user data from the virtual machines. Although a VF can access full GPU capabilities at its own GPU partition, it does not have access to the dedicated local memory of its sibling VFs.

 

 

Uncompromising Support for APIs and Features

The AMD Multiuser GPU technology exposes all graphics functionality of the GPU to the VF at its partition allowing for not only full support for graphics APIs like DirectX and OpenGL but also GPU compute APIs like OpenCL™.  Code written in these standards for the physical device need not be adapted or altered to function in the virtual environment. AMD is the first GPU vendor to support hardware-based native GPU compute features within the virtual environment. Since VFs are allowed access to all of the GPU’s rendering resources during their respective time slices, the need to perform post-processing operations to partition data or tasks is not necessary.

  

AMD operates on the principle of creating customer-centric designs, offering useful features and allowing customers to build usages around these features. Limits are added to control quality, not to constrain utility. Radeon Pro professional graphics, AMD’s workstation brand of graphics products, can drive up to six displays per GPU as a standard offering on select AMD Radeon Pro W-series products. Because the Multiuser GPU resides among the FirePro brand of products, the ability to drive up to six displays is an inherent feature. Multiuser GPU products extend this feature by allowing each VF to drive up to six displays within the virtual machine (note that this may be dependent on the remoting protocol and client being used).

 

 

Conclusion

The desire to share storage and network resources sparked innovation of technologies for these devices. The need to centralize all these resources and to secure them in a remote datacenter continues to drive the migration to virtualization. GPU virtualization is a relatively late participant in this migration with early proprietary software-based solutions offering limited GPU capabilities. To become ubiquitous, GPU virtualization technology has to be transparent and standardized, giving users near-desktop experiences without alerting to the fact that they are in a virtualized environment.

 

AMD Multiuser GPUs push GPU virtualization closer to complete transparency and ubiquity by innovating with a hardware-based solution with conformance to the virtualization industry standard, making it easy 

to be adopted and integrated into the existing hypervisor ecosystems.

The financial services industry is no stranger to virtualization, having already come to appreciate the advantages it offers for satisfying important IT requirements such as centralized data security, enhanced mobility, and improved disaster recovery capability. The advent of Microsoft’s new NVv4 instance for Microsoft Azure with fractional GPU capability now has the potential to make it feasible to expand the use cases, practicality, and opportunities to use virtual machines (VMs) to support finance operations.

 

The Virtualization Challenge

One of the barriers to broad adoption of virtualization across many more essential financial applications has been the fact that most widely used software solutions such as trading consoles and visual analytics workstations require GPU support to ensure responsive interactivity under real-time demands. Prior to NVv4, this was only possible by providing each user’s computer or workstation with access to a full, dedicated GPU in the data center. This was highly inefficient, as many applications really only require a small, but nonetheless critical, amount of GPU processing to deliver a great user experience. Thus, the approach was expensive on a per-user basis and did not sufficiently improve the maintenance burden on IT departments. The need to offer the highest level of security for these environments has further complicated the switch to virtualized topologies.

 

NVv4 Changes the Virtualization Equation

Azure NVv4 instances powered by AMD 2nd Gen EPYCTM Processors and AMD Radeon InstinctTM GPUs tackles these challenges. Financial services organizations can deploy cost-effective, fully cloud-based desktop environments that meet the performance, flexibility, security, and cost requirements of their critical applications. NVv4 also addresses the management requirements and security standards demanded by IT management and corporate governance. Specific benefits include:

 

  • AMD’s SR-IOV technologies enable IT managers to deliver the right amount of GPU service to individual desktops and workstations based on application needs while sharing a high-powered GPU among multiple users.
  • Four AMD powered NVv4 options make it possible to provide configurations that align with the particular computing workloads of different users.
  • VMs such as Azure control data because data never leaves the datacenter; only pixel information is sent to the device.
  • With AMD’ SR-IOV-based GPU virtualization architecture, each virtual desktop is physically isolated, even when a single GPU is shared by multiple users.
  • Based in the Cloud, Azure can reduce reliance and expenditure on physical IT infrastructure such as on-premises data centers.
  • NVv4 offers instances that can support 4K displays, 60hz screen refresh rates, and multi-monitor support for up to 4 monitors. 

 

Let’s consider just a few of the use cases that are now possible to the financial services sector.

 

Branch offices

Azure is centralized in the Cloud, so it enables IT departments of large financial organizations to remotely deliver and update applications and roll-out security patches. This can also help IT retain greater situational awareness of their entire distributed environment, which may include hundreds or thousands of branch offices, affording improved control and compliance oversight. With greater visibility, IT administrators can better optimize usage of costly software licenses and better manage costs. 

 

Azure supports end-users with an ultra-low-latency global data backbone that delivers a highly productive experience. The combination of AMD enterprise-grade CPU and GPU hardware with the NVv4 Windows® 10 virtual instance helps ensure optimal compression for remote protocols that can overcome local limitations in networking and bandwidth, relieving IT of the need to install and modify leased offices. As tablets and other portable devices become common in local banks, a virtualized approach makes it possible for such devices to access powerful tools, enabling staff to assist customers from convenient, comfortable locations rather than behind a bulky workstation at a fixed desk.  

 

Trading environments

The Windows 10 environment and key business applications such as Bloomberg, Capital IQ, FactSet, and Thomson Reuters Eikon, all require GPU support to deliver the responsive, low-latency interactive experience users such as traders demand. Powered by the combination of AMD 2nd Gen EPYC processors and AMD Radeon Instinct GPUs, NVv4 instances address that challenge while providing IT managers with flexibility to choose the right-sized configuration for different types of users.  Unlike on-premises data centers, where IT managers must purchase hardware and licenses, then install and service servers, NVv4 enables IT managers to simply and quickly provision resources from the Cloud when adding new users to the workforce.  

 

Data Security and Regulatory Compliance

Secure remote access provides financial services companies the knowledge that data is locally replicated and can be backed up centrally in the data center avoiding unmanaged end-points.

 

Business Continuity and Disaster Recovery 

In today’s electronic trading environments, downtime can lead to missed opportunities and significant financial loss. If an office, municipality or large region is impacted by a natural or man-made disruption, a virtualized infrastructure can provide critical redundancy.  It can help ensure that vital data sources, compute/simulation resources, real-time analytics tools, and trading desktops remain online and accessible, enabling staff to work remotely and securely. Azure guaranteed Service Level Agreements (SLAs) for VMs typically guarantee in excess of 99.9 percent availability. 

 

Channel Partner Access

Financial products are often sold via brokers or agents, particularly in the consumer insurance and mortgage sectors. Virtualization can allow financial institutions to provide sales channel partners with secure, limited, ring-fenced access to applications or data as needed. This is critical to maintaining compliance with FSA and GDPR legislation. Azure has a proven track record of supporting the compliance needs of enterprise, global financial services, and banking organizations.

 

The Financial services industry faces some of the most challenging IT configuration and management issues. The flexibility of NVv4 is well worth a look by those looking to effectively streamline some of that complexity and better control costs, without sacrificing performance.

 

Other resources to consider:

 

George Watkins is a Product Marketing Manager for AMD. His postings are his own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

Microsoft’s announcement of its new NVv4 virtual desktop instances got me thinking about the many industries that may benefit from expanding virtualization. With fractional GPU functionality built on AMD Radeon GPUs, NVv4 suddenly makes it feasible to apply Desktop as a Service (DaaS) to use cases previously burdened with compromises. So, over my next few blogs, I’ll explore some of those industries, beginning with a favorite of mine, Education.

IT Managers in education work magic, forever balancing technical progress, rising user expectations, and, above all, cost. Microsoft Azure NVv4 is exciting because it addresses the breadth of those challenges. By making it possible to share GPU resources in a third-party, cloud-based managed data center, NVv4 enables education IT to:

  • reduce the need to invest in, manage, and upgrade expensive private data centers
  • define and scale virtual data centers to deal with the evolving demands
  • optimize usage of computing resources
  • deliver a custom-fit, great user experience to the differing needs of students and faculty
  • increase security and accessibility on- and off-campus

DaaS--The Right-Sized Approach to Education IT Needs

DaaS shares the appealing capabilities of on-premises VDI (Virtual Desktop Infrastructure), but with the massive added benefit that a third-party provider like Azure now designs, procures, deploys, and manages all the necessary hardware and VDI software. Education facilities instead rent cloud-based services on a monthly basis. 

IT operations can switch from a rigid CAPEX spending model to a flexible OPEX model, paying for only what they use. This may be the answer to the reduced demand of summer holidays, term breaks, and variations in teaching and learning hours. 

Device Flexibility

Virtual desktops are accessible from students’ own devices, regardless of technical specifications. This is possible because all performance and data are in the Cloud. Only the final info needed for display is sent to the user. This can extend the life of devices and make it possible to support affordable low-power PCs, Chromebooks, or tablets without the concern of performance or application compatibility issues. In fact, students can generally choose between Macs, PCs, or Chromebooks for courses without compatibility concerns. IT administrators can be freed from maintaining physical PCs and workstations while centralization also simplifies the management of software licenses. 

 

Fractional GPU with AMD Changes the Equation for Education

Until NVv4 it was only possible to choose between expensive full-GPU, high-specification VMs or non-GPU VMs. Configurations without any GPU don’t meet the demands of even a basic modern web browser. While a full GPU made sense for high-end workstation applications, that level of service was costly overkill for users of basic productivity software and collaboration who require only a small portion of a GPU to enjoy a great experience. 

GPU partitioning in  Azure NVv4 instances allows IT administrators to fit the needs of application and course requirements. For example, initial undergraduate courses using SolidWorks are unlikely to have the same demanding requirements as professionals in CAD/CAM industries. An NVv4 option with 4GB of GPU is usually sufficient to provide a high-quality experience at a lower cost for many engineering applications as well as Windows 10 and video streaming. Larger GPU options are also available to support heavyweight users and researchers doing more intensive CAD work or sophisticated CFD (Computational Fluid Dynamics) simulations.  

 

The Tools for Great User Experiences

Remote display application and protocols are key to good user experiences with VDI/DaaS in the Cloud and the NVv4 does not disappoint with Windows Remote Desktop (RDP) 10, Teradici PCoIP, and Citrix HDX 3D Pro for remoting flexibility, regardless of the intended use case. The AMD Radeon GPUs also support native graphics APIs like DirectX 9 through to 12, OpenGL 4.6, and Vulkan 1.1 ensuring a true graphics experience in the Cloud. AMD Radeon Pro professional graphics drivers are included license-free with all AMD GPU enabled Azure instances, with no restrictions on the number of users for multi-user Windows Virtual Desktop and Remote Desktop Session Host, providing IT departments with administrative freedom. 

Addressing the Modern Education Environment

Data Security
Virtual desktop environments are essentially sandboxed and centralized, with Azure running the Hyper-V hypervisor. IT administrators no longer need to worry about the security patching of BYOD laptops and can be assured that educational resources are not abused for gaming, bitcoin mining, or accessing inappropriate material. Azure’s regions and data controls are already proven and trusted for handling sensitive research projects and data in collaboration with military, government, and industrial collaborators.

Increased Access with Virtualized Classrooms, Labs, and Distance Learning

Students can work anywhere--in libraries, residence halls, off-site, or around the globe. NVv4 helps schools overcome weather, distance, time, and increase their capacity to remove barriers to access through online programs. Curricula can be rapidly refreshed, centrally deployed, and managed to enable universities and high schools to provide online courses, and to deploy new course materials and resources instantly. Azure’s high-availability guarantees and regional data centers to provide low latency access globally.  Courses in other time zones may also rely on Microsoft supported infrastructure avoiding not only the need for hardware but also out of hours IT support. 

Support demanding graphical, collaborative and processing-intensive curricula

The new NVv4 instances are powered by the 64-core AMD EPYC 7742 CPU and the AMD Radeon Instinct MI25 GPU, with GPU sizes between 2GB-8GB available and full AMD Radeon Pro professional graphics drivers. By removing the need for students to be tied to high-performance workstations, even design, engineering, animation, and visual effects courses can be supported virtually and use professional 3D software applications including Dassault Systèmes SolidWorks and Catia; Autodesk, PTC, Siemens NX, and Adobe Creative Cloud.  NVv4 similarly delivers a great foundation for modern collaboration applications with rich media. 

 

I believe that NVv4 has the potential to dramatically reshape the IT landscape for education. It creates remarkable new opportunities for IT managers to better balance what have been competing demands for up-to-date technology, security, cost management, and great user experiences for faculty and students.  

Find out more

If you’d like to find out more, please visit Amd.com [hyperlink] 

Additional links 

 

George Watkins is a Product Marketing Manager for AMD. His postings are his own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

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other resources:

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The information contained in blog represents the view of AMD or the third-party presenter as of the date presented. AMD and/or the third-party presenters have no obligation to update any forward-looking content in the above presentations. AMD is not responsible for the content of any third-party presentations and does not necessarily endorse the comments made therein.

 

George Watkins is a Product Marketing Manager for AMD. His postings are his own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

Virtualized environments can pose some challenges for companies. In order to bring a more consistent and user friendly experience to virtual environments, AMD and Microsoft have been working together to offer a whole new cloud experience for desktop and workstation users.

 

Microsoft Azure NVv4 instances are the first desktop as a service (DaaS) Virtual Machines (VMs) powered by the combination of 2nd Gen AMD EPYC processors and AMD Radeon Instinct GPUs. The NVv4, as of today, is now generally available to the public.

 

NVv4 represents a convergence of innovative technologies to make modern desktop experiences possible from the cloud. Enterprises can deploy affordable, cloud-native GPU-accelerated desktop environments that meet the performance and flexibility demands needed for high productivity of their employees. Just as important, NVv4 also offers state-of-the-art IT management tools to help drive success of IT organizations.

 

How is this possible? NVv4 instances are built on three fundamental pillars to enable cloud-native modern desktop and workstation experiences.

 

GPU-Accelerated Performance

Today’s digital workforce relies on modern applications. Modern applications are built with GPU acceleration at their core. From the most powerful 3D design tools, to common office productivity tools, and even web browsing, everyday applications are designed to require or benefit from graphics acceleration support built in. In other words, virtual machines without GPU acceleration will often struggle with some of the most common desktop tasks.

 

As the first VMs on Azure to take advantage of AMD’s SR-IOV technology to enable GPU partitioning, NVv4 provides IT decision-makers with four VM options calibrated to meet the variety of use cases in the modern workplace. Whether they are a professional running a workstation-class design application or support staff using Microsoft Office 365, all users receive the performance and reliability of 2nd Gen AMD EPYC processors and Radeon Instinct GPUs. ISV certifications and optimizations for professional 3D applications further reinforce the user experience.

 

Support for the latest Windows 10, Windows Server and Windows 10 Enterprise multi-session operating systems provides IT with the flexibility to specify single- or multi-session configurations as needs dictate. Even when the GPU is partitioned, the individual user’s experience is indistinguishable from the experience of a locally installed GPU to which they are accustomed.

 

IT managers can continue to rely on the traditional remote protocols, management, and administration tools they prefer. NVv4 instances are fully supported by Windows Virtual Desktop, Citrix Cloud, Teradici Cloud Access and Workspot Cloud VDI so the migration to Azure is both smooth and familiar.

 

“The flexibility that Azure NVv4 with AMD-powered GPU partitioning provides for users to share and access GPU resources as needed is a valuable feature that we see will benefit many Teradici customers. We are excited to be working with Microsoft and AMD to enable more flexible, cost-effective GPU options for virtual desktop and virtual workstation use cases such as AEC.”

– Ziad Lammam, Vice President of Product Management at Teradici

 

Uncompromised Security

Security is at the core of nearly every IT conversation. In an infrastructure where resources are shared across users and services, companies need to be confident that individual users data is fully protected. While Azure is built on world-class security technologies, traditional GPUs

 

Security runs deep into the hardware of AMD-powered Azure environments. While traditional GPUs rely on software techniques for security in virtualized environments, NVv4 is powered by SR-IOV-based GPU virtualization, enabling isolation of PCIe hardware resources to prevent unauthorized access to the data of one VM by users of other VMs. Each VM can only access the physical resource that has been allocated to it. Each VM is physically isolated from others, even when a single GPU is shared by multiple users. SR-IOV is recognised and established in the industry as one of the key standards for resource isolation – that’s why Microsoft is including  this technology as part of its comprehensive plan to keep its customers safe and protected when virtualised.

 

"The diversity of the new AMD-based Workspot cloud desktops on Microsoft Azure is a huge deal for us. Based on the application requirements of each engineer, we can dedicate all or a fraction of the AMD GPU to their Workspot workstation on Azure. This finer resolution of control gives us the financial edge we need to move more people to Workspot cloud desktops on Azure and increase our overall productivity."

– Eric Quinn, CTO at C & S Companies

 

Cloud-like Affordability

One of the biggest promises of cloud is that businesses can reduce their cost by renting exactly what they need. Yet for businesses looking to deploy GPU-accelerated VMs, this was not possible. Prior to NVv4, users could only choose between more expensive full-GPU VMs or non-GPU VMs. Even if the user didn’t need the entire performance headroom of a full GPU, they would be required to rent it. While the cost of a full GPU could be justified for the highest-end workstation workloads, most desktop experiences need a fraction of the GPU for optimal experience.

 

One of the key benefits of AMD-powered GPU partitioning in Azure is the ability to deliver fractions of a GPU at more affordable price points. Four AMD-powered NVv4 options are available to IT managers, making it possible to provide virtual desktop configurations that perfectly meet the particular computing workloads of different users. NVv4 instances can deliver GPU-powered desktop experiences that enable the GPU to be configured to be used by eight, four, two, or a single user as dictated by their application needs.

 

“As more organizations start migrating Citrix workloads to Microsoft Azure, they want to ensure that they’re delivering that same level of experience as their previous on-prem deployments. We’re excited to be partnering with AMD and Microsoft with the release NVv4 instance, as this ensures organizations can deliver graphically accelerated Citrix Workspaces with superior user experiences while also optimizing their costs.”

– Nitin Sharma, Sr Product Marketing Manager for Workspace Services at Citrix

 

Promises Fulfilled

AMD CPU and GPU powered NVv4 instances are the first GPU-accelerated virtual desktops for Azure and provides businesses with productivity, the absolute requirement for security, and the ever-present pressure to manage costs, all while providing users with an adaptable, flexible, high-performance cloud-based work environment that addresses the breadth of expectations of the modern workplace.

 

Businesses interested in assessing and testing DaaS environments for their operations can work with Microsoft partners like Cloud Jumper and Workspot to ensure professional and experienced teams who can help assess your business needs every step of the way from POC to deployment and migration.

 

Find out more:

 

George Watkins is a Product Marketing Manager for AMD. His postings are his own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

A few months ago at Microsoft Ignite in the AMD booth, I had the opportunity to showcase the first GPU partitioned and shared instances (NVv4) available for Microsoft’s Azure cloud featuring the AMD Radeon Instinct MI25 accelerator, along with AMD’s other EUC (End User Computing) and data center products. News about the Microsoft and IGEL partnership relating to WVD (Windows Virtual Desktop) also attracted interest from our Cloud, Citrix and related customers. Although WVD has been available in preview, no Linux-based WVD client had been available which resulted in increased interest in the IGEL offering. And at the recent Disrupt 2020 event, IGEL announced the first Linux client to support WVD. The Microsoft SDK that makes this integration possible has the potential to enable other thin-client vendors to offer their own solution.

 

While the use of AMD CPUs and server GPUs is well-known, AMD is also a major player in providing the CPU and graphics/GPU hardware within many of the most popular thin clients.

 

The joint IGEL and Microsoft announcement was particularly satisfying for me as it heavily featured IGEL’s flagship UD7 client targeted at graphical use cases which is built around AMD technologies. For example, the technical specifications for the UD7 client features the AMD Embedded RX-216GD 1.6 GHz (Dual-Core) up to 3.0 GHz (boost mode), system on a chip (SoC). With the option for an additional graphics card, the AMD Embedded Radeon™ E9173 discrete GPU can extend the UD7 to support the simultaneous use of up to four digital monitors at 60 Hz by DisplayPort (two in 4K and two in 2K). The flagship UD7 client also features IGEL’s latest security enhancements -- a benefit for scenarios when security is a concern for thin clients. 

 

Last week at IGEL Disrupt Munich, a new version of the UD3 client was announced on BrianMadden.com. The UD3 is supported by a specially optimized AMD Ryzen Embedded R1505G that: uses less power (about 10 watts); features hardware optimizations for PCoIP (PC over IP) Ultra; and leverages the AMD Secure Processor feature checks to help assure the UEFI is signed by IGEL. The availability is expected May 2020, but in the meantime information currently exists about the specifications and IGEL solution architect blogs, including a blog by Fredrik Brattstig.

 

My role at AMD is largely associated with evaluating the performance of our Data Center and Cloud products including AMD Radeon Pro V340 and AMD Radeon Instinct MI25 server GPUs. The evaluations are conducted within the context of the protocols and EUC/VDI environments used in scenarios featuring Azure, RDP, Citrix, VMware, and Teradici. Most remoting protocols have a feature often referred to as “Back-pressure” – a process whereby the end-client is aware of whether it is keeping up with the server frame rate and alerts the server accordingly. It’s widely known that there’s no point churning out frames if the end-point can’t handle the rate. So it’s important to have a suitably powerful end-point that can become the most significant factor in the overall user experience. IGEL, supported by AMD solutions, has proved very popular, You can discover from IGEL about the use cases and features of the UD3 and UD7.

 

The IGEL and Microsoft partnership plus WVD support along the AMD enabled NVv4 Azure instances were all featured by the independent blogger, Bas Van Kaam. The recommended blog offers a suitable summary of Ignite and can be found here.

 

Now that these major events have concluded, I’m eager to get back in the AMD lab to “kick the tires” of WVD and the NVv4 Azure instances with the WVD supported IGEL UD7. My goal is to blog about my findings, but I’m eager to discover others’ experiences with thin clients, especially if there are additional factors for consideration. If you want to try out NVv4 with WVD, I recommend a useful video guide available from Microsoft’s Stefan Georgiev on  YouTube.

 

Recommended Links

 

Joe DaSilva is a Cloud Graphics Solutions Architect for AMD. His/her postings are his/her own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

AMD GPUs deliver the first shared GPU instances for Microsoft Azure – NVv4 instances

Today, the first Azure instances utilising GPU partitioning technology became available. These instances effectively enable a large server GPU to be partitioned, supplying VMs with an appropriately sized GPU, and opening the way for potential savings in the cost for GPU-enabled cloud VMs.

 

Key to adoption of AMD GPUs by Microsoft Azure was the alignment of our SR-IOV based MxGPU hardware-sharing technologies to Microsoft Hyper-V’s own GPU-P technologies. This is clear validation of our strategy at AMD to work with Microsoft over many years to align with their roadmap resulting in the first GPU sharing solution on Azure, acceptable in terms of user segregation, security features and quality of service. Our virtualised GPU sharing technologies have already been proven with other hypervisors including VMware ESXi and the Citrix Hypervisor (XenServer). This is however the first time GPU sharing has been enabled for a Hyper-V based platform with Azure.

The result is a portfolio of instances leveraging both AMD CPUs and GPUs that are sized to the realistic needs of users; ranging from smaller instances that align to the needs of Office workers or Mobile CAD workstations (2 and 4 GB equivalent GPU resource) to larger instances that can support heavier graphical needs and session sharing like needs. AMD professional GPU drivers are offered free along with these instances.

 

vCPUMemoryGPU memoryAzure network
Standard_NV4as_v4414 GB2 GB50 Gbps
Standard_NV8as_v4828 GB4 GB50 Gbps
Standard_NV16as_v41656 GB8 GB50 Gbps
Standard_NV32as_v432112 GB16 GB50 Gbps

 

Initially NVv4 instances will be available in Azure Regions early next year in the South Central US and West Europe Azure regions.

 

Sign-up for preview using this link:  https://aka.ms/NVv4Signup

 

AMD Technology enables Microsoft Azure at Ignite 2019 Microsoft the preview; the interest it attracted in the booth but also in the End User Computing (EUC) and similar communities was fantastic, and it was great to speak to so many users about their enthusiasm for the options. I was cheered to see a blog by cloud community expert Marius Sandbu that covered the announcement but also caught the spirit of what we had hoped to convey.

 

Useful Links:

 

 

AMD at Microsoft Ignite

 

 

 

 

Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

 

George Watkins is a Datacenter GPU Marketing Manager for AMD. His postings are his own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied.

AMD based Microsoft Azure virtual desktops deliver a workstation-class experience in the Cloud

 

Autodesk University is the place to be for professional architects, designers, engineers, and media creators. Of course, AMD will be there, returning as a Gold Sponsor of this important event to provide demonstrations of our most powerful desktop processors and graphics cards, to discuss your biggest challenges, and to reveal the latest technology innovations that enhance the workstation experience.

 

Taking centre stage in our booth, AE310, will be live demonstrations of the Microsoft Azure stack, leveraging the new NVv4 instances. This is the first Windows Azure virtual desktop to be supported by both 2nd Gen AMD EPYC processors and Radeon Instinct MI25 GPUs. If you are one of those people who designs, makes and builds the world around us and relies on the highest performance from applications like Autodesk to make things happen, then you owe it to yourself to learn more about the NVv4 instance.

 

Wondering what NVv4 stands for? “N” = GPU Accelerated VM family in Azure. “V” = Visualization. “4” = Generation 4 – which means the NVv4 is the current latest generation of GPU-enabled virtual desktops services from Azure.

 

Be more productive and collaborate by extending workstations to the Cloud

Modern-day designers, architects, and engineers demand the most of their critical tools. Whether in the office or at home, traveling or onsite, they need a workstation-class experience that provides flexibility and reliability no matter where in the world a project might take them. The NVv4 virtual desktops bring the full power of a traditional workstation configuration to bear whenever and wherever it’s needed. AMD GPU-enabled NVv4 virtual desktops make it possible to finally overcome the difficulty of balancing performance, mobility, and cost when addressing traditional Architecture, Engineering, and Construction (AEC) workloads.

 

Just what are Microsoft Azure NVv4 instances?

The NVv4 is a new, virtual desktop solution in Microsoft Azure that takes advantage of SR-IOV technologies (Single-root input/output virtualization) to introduce, for the first time, GPU-partitioning (or GPU-P). This gives customers maximum flexibility and choice by providing dedicated CPU/GPU-supported virtual desktops that best suit their workloads and price points. In fact, NVv4 will offer four distinct instance options to choose from, scaled to share a single GPU’s resources among as many as eight Virtual Machines. 

 

Alternatively, IT managers can maximize the user density of NVv4 with Windows 10 EVD, supported by Windows Virtual Desktop and available plug-ins from Citrix and Teradici. Anyone interested in trying the NVv4 experience for themselves can do so by signing up for AMD’s customer preview.

 

What will AMD be showing at AU?

Throughout Autodesk University, we will be showcasing our preliminary test environment, based on the planned NVv4 hardware and software stack, available in Microsoft Azure. You will get the chance to see a variety of the latest Autodesk applications for AEC and CAD workloads. AU19 will be a great opportunity to speak to the AMD team and explore how AMD-enabled virtual desktops in Microsoft Azure may help your organization. 

 

 

George Watkins is a Datacenter GPU Marketing Manager for AMD. His/her postings are his/her own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied. 

AMD technology makes GPU enabled virtual desktops possible across the entire Enterprise!  

 

Talk about being in the right place at the right time! My first opportunity to participate in the 2019 Microsoft Ignite conference, promises to set a new highwater mark for impactful demonstrations, learning opportunities, and meaningful collaboration between AMD technology and the Microsoft ecosystem.

 

This year the AMD booth will be packed with technologies and demonstrations of many of the latest AMD solutions with Microsoft, including the latest high-performance laptops and virtual desktops. For me though, the highlight at Ignite is the exciting news around Microsoft Azure NVv4 instances; the first Windows Azure virtual desktop supported by 2nd gen AMD EPYCTM processors and Radeon InstinctTM GPUs.

 

Wondering what does NVv4 stands for? “N” = GPU Accelerated VM family in Azure “V” = Visualization “4” = Generation 4 – which means the NVv4 is the latest generation of GPU enabled virtual desktops services from Azure.

 

Modern day applications want more

This is an important distinction because many modern productivity applications like Office 365, video conferencing and web browsing are designed to harness the GPU to deliver the best possible application experience. Many non-GPU VMs however struggle to deliver that experience while previous GPU-accelerated VMs could only be configured, and priced, to deliver a full GPU as a workstation experience – making them too costly for everyday users.   

 

Re-evaluate GPU enabled Virtual desktops

The introduction of AMD powered NVv4 instances is shifting the expectations for VM deployments and is sure to have IT managers taking note. What’s changed? Well, The NVv4 instance is the first VM on Microsoft Azure to take advantage of SR-IOV technologies (Single-root input/output virtualization) and introduces GPU partitioning across four new options. This gives customers greater flexibility, enabling the entire enterprise to enjoy dedicated CPU/GPU virtual desktops, delivering the best application experience regardless of the workloads. In fact, NVv4 will offer four distinct instance options to choose from, scaled to share a single GPU’s resources among as many as eight Virtual Machines. Alternatively, IT managers can maximize the user density of NVv4 with Windows 10 multi-sessions, supported by Windows Virtual Desktop with available plug-ins from Citrix and Teradici. Anyone interested in trying the NVv4 experience for themselves can do so by signing up to customer preview.

 

Attending Ignite?

During Ignite, there will be a great opportunity to speak to our team about the benefits of all the AMD supported Azure instances and have the chance to sign up to the NVv4 customer preview at the AMD booth #249. If you want to learn more about the technologies powering NVv4 you might like to join these AMD sessions: Technical (BRK1114, Thursday 7th Nov, 11:30am),Hub (THR1086, 9am, Tuesday 5th Nov) and a NVv4 dedicated session by Microsoft (BRK3121) if you are lucky enough to be there in person.

 

From Azure to Windows, we love Microsoft! Come visit AMD  Booth #249 and experience all of our technology demonstrations and discuss how we can address your business needs!

 virtualization, single root input/output virtualization or SR-IOV (Single-root input/output virtualization) is a specification that allows the isolation of PCI Express resources between different users. It is already the standard used to share networking resources (NICs) and secure network traffic. Each resource has Virtual Functions (VF) associated and each VM (Virtual machine) can only access the physical resource via its own allocated VF.

 

 

 

The AMD MxGPU (GPU sharing technology) is the industry’s first SR-IOV based GPU sharing technology designed for cloud and datacenter. So why did we choose SR-IOV?

 

 

      
  • Industry standard. SR-IOV is the long-established industry standard for virtualising PCIE devices. As such, the standards are openly scrutinised for security.
  •   
  • The isolation provided by VFs helps ensure each VM is isolated from other e.g. memory is secured and not shared.
  •   
  • Long-term we believe SR-IOV is a base technology that will allow for scalability and higher user densities long term as a technology that minimises context switching overheads.
  •   
  • Stability and reliability. SR-IOV allows us to provide each VM with its own dedicated share of a GPU and it does not compete with other users, helping ensure the resource available is consistent and the same; users can avoid the unreliability associated with noisy neighbours and experience deterministic QoS.

 

 

 

 

SR-IOV a technology that has evolved with and for cloud

 

Back in 2009. veteran blogger Scott Lowe wrote an introduction to SR-IOV predicting it would become mainstream, it’s great context to the environment and technology of the time. Whilst we could have accelerated to market using a bespoke proprietary memory management unit (MMU), we instead chose to work with the major hardware, hypervisor and operating system vendors to evolve the technologies to an industry wide fit for our long-term needs.

 

 

The evolution of SR-IOV was carefully managed and in2016 was able AMD to release the world’s first SR-IOV based GPU sharing solution for cloud and virtualisation. Beyond the obvious security and quality benefits of aligning to the core technology, the standards offer potential long-term scalability that a bespoke implementation wouldn’t have offered us.

 

 

We are seeing increasing rewards from this approach now, as other vendors -- particularly Microsoft -- have placed SR-IOV at the core of their technologies and infrastructure. This alignment has streamlined our joint projects, leading to the announcement of MXGPU into the Azure cloud to enable cost-effectively sized and priced GPU enabled VMs. (You can register interest with Microsoft in the release availability, here.) MxGPU SR-IOV support is also available and proven for Citrix XenServer, XenDesktop and XenApp, VMware ESXi, Horizon View and open source KVM. Read more, here.

 

 

 

 

SR-IOV and MXGPU at Ignite

 

Our product management team will be at Microsoft Ignite (4-8 November), and you can find us on booth #249. You might also like to join these AMD sessions: technical session (BRK1114, Friday 8th Nov, 9am) and hub session (THR1086, 9am, Tuesday 5th Nov) if you are lucky enough to be there in person.

 

 

 

 

Learn More

 

 

      
  • Microsoft high commitment and investment in integrating the SR-IOV standards into the core of their platforms such as Windows and Hyper-V is significant and as such they’ve published significant information on this approach including overviews and architectural deep-dives.
  •   
  • Our hypervisor and virtualisation partners have also been investing in core SR-IOV technologies, as well as releasing information as to the benefits and reasons for this approach. In September 2018, Citrix released XenServer 7.6; the release notes are available to read, amongst other features they cover Citrix’s and XenServer’s adoption of SR-IOV for networking (NICs – Network Interface Cards).  

 

 

 

 

 

The SR-IOV standard

 

The SR-IOV standard is controlled and maintained by the PCI-SIG foundation. The regulation and scrutiny of the standard is maintained with cross-industry membership and funding, alongside a compliance programme and certified integrator list.

 

 

MXGPU more than SR-IOV

 

Of course, there is more to MXGPU than SR-IOV, it is just one of core technologies on top of which we have built our GPU sharing and virtualisation products.  We are however pleased that we were the first vendor to achieve GPU sharing the SR-IOV ‘gold-standard’.

There have been numerous opinions offered from all corners of the gaming community about the impact of Google Stadia. Gaming and business journalists, bloggers, and avid gamers all have opinions to share. And while a few revert to familiar hardware “spec” comparisons to gauge the value of new technology, the introduction of Google Stadia is clearly about much more. Google Stadia marks an evolution of the gaming landscape that’ll rapidly reshape the industry.

 

In the short time since Stadia was announced, several themes have emerged that will likely drive increased cloud gaming adoption.

  • Consistent Premium Performance
  • Transparent Maintenance
  • On-Demand Gaming & Social Integration
  • Device Access & Mobility
  • Cloud gaming value chain
  • Subscription based services

 

While this discussion is primarily based on Google Stadia, many of the value propositions introduced can be applied more generally to cloud gaming services such as Microsoft xCloud and Sony’s PlayStation Now.

 

Below we’ll introduce each theme and in future blogs dive deeper into each to explore their impact on the industry.

 

Consistent Premium Performance

Performance and hardware specs will continue to drive conversation near term for two reasons: the industry is familiar with it, and it can be can measured. While this understanding is important, moving forward the conversation will likely shift to focus on delivering a consistent premium experience. Stadia allows gamers to reconsider the entirety of the gaming experience and the context within which we view performance. 

 

The choice of custom AMD “Vega”-based GPUs as a starting point for this service launch reflects Google’s strong commitment to what makes gamers happy and a deep understanding of what makes datacenters tick. Gaming is a part of the AMD DNA, delivering high performance GPUs for the latest game consoles, high-end gaming PCs, and the datacenter.  The AMD “Vega”-based GPUs for Stadia are a proven platform featuring 56 compute units, up to 10.7 teraflops, integrated HBM2 memory, and with the Vulkan® high-performance real-time 3D graphics API part of the driver. That’s easily more power than the top two previous generation consoles combined and a foundation for success that can deliver a next-generation console experience today1.

 

But for the player, all that matters is the experience, which at resolutions up to 4K and 60 frames per second, with HDR and surround sound, promises to be fantastic and substantially better than what many gamers enjoy today.

 

Transparent Maintenance

How many times has a user tried to launch a game only to be met with a time-consuming multi-gigabyte patch? With cloud gaming, software maintenance happens in the background, transparent to the user. In addition, the centralized design of Stadia also means they will not have to worry about hardware upgrades. The datacenter can be upgraded to keep pace with changing requirements, transparent to the user. In short, more play, less hassle.

 

On-Demand Gaming and Social Integration

Stadia will enable the ~200 million people who watch game-related content such as trailers and live streams on YouTube to lean into their enthusiasm and join the action with just a tap on their phone, tablet, or computer. Social integration allows for instant broadcasting, archiving, and sharing you and your teams’ latest achievements. E-sports fans and stream audiences can simply click a link on their favorite social media site and instantly launch into the latest titles.

 

Game downloads are a thing of the past, like music and movies before it, many games are now available “on-demand”. 

 

Device Access and Mobility

Google Stadia delivers the AAA gaming experience to the widest audience. That means great games, streamed via standard Internet connections, to a variety of devices, and all while enhancing the social aspects of and accessibility to those experiences to better match the preferences of today’s consumer.  

 

This vision is made possible by shifting focus of the gaming world to the datacenter. The organizing principle of gaming is the datacenter rather than the individual’s device. Google’s 7500 edge nodes worldwide will put powerful gaming hardware essentially everywhere and in reach of virtually everyone.

 

With cloud gaming, if you need to take your gaming on the go, no need to start over. You can simply save state on your home theater or Chromebook and pick up seamlessly on your mobile device. That flexibility promises to change how players weave gaming into our everyday lives.

 

Evolving Business Model 

The transition of gaming to the Cloud will impact many companies including console providers, game developers, and publishers. Traditionally, publishers have had a variety of platform options on which to distribute their game titles and reach their audience. One challenge they have faced however is the large fees required to gain access to each distinct platform. The introduction of new, high-performance cloud platforms like Stadia gives more choice for the game publishers.

 

Another interesting consideration which Stadia has introduced for many game developers and publishers is the access to nearly unlimited resources to build their games on. In the past, console hardware has tended to follow a slower refresh rate than gaming PCs. As a result, AAA games that appear later in a console cycle had to be developed to support both older console technologies as well as more recent platforms.  The resource demands sometimes restricted what a game developer could create. It could be proposed that the datacenter is the console when speaking about cloud; better still, it can be continuously updated to maintain the highest levels of performance removing the need to buy the latest GPUs. By default they have access to the best gaming platform for their next blockbuster title. 

 

Manufacturers building game-specific hardware including consoles have also recognized the potential of cloud gaming. They can see a future where they have an opportunity to shift their efforts away from developing hardware with costly components and fighting expensive PR battles centered on hardware superiority, and instead drive wholeheartedly at creating the best games environment. Datacenter-based gaming provides a new, more cost-efficient and sustainable direction that can consolidate and balance costs. It means the business of games can stop competing on specs and instead compete on content. That’s something every gamer can appreciate.

 

Subscription Based Gaming

Google Stadia breathes new life into the gaming conversation, triggering a dialogue about the liberation offered by cross-platform play, blurring the lines between gameplay viewers and players, and establishing a flexible infrastructure that adapts to the innovation of developers.

 

This is a conversation I'm excited to continue over the coming months.

 

George Watkins I Marketing Manager I Datacenter GPU BU

These views are my own and do not reflect that AMD.

 

©2019 Advanced Micro Devices, Inc. All rights reserved. AMD, the AMD Arrow logo, Radeon, and combinations thereof are tradema##rks of Advanced Micro Devices, Inc. Thunderbolt is a trademark of Intel Corporation or its subsidiaries in the U.S. and/or other countries. Other product names used in this publication are for identification purposes only and may be trademarks of their respective companies.

 

Footnotes:

1) 4th September 2019, based on PS4 Pro GPU performance (4.2 TFLOPS) and Xbox One X GPU performance (6 TFLOPs) compared to With Google Stadia GPU performance (10.7 teraflops)

https://www.digitaltrends.com/gaming/xbox-one-x-vs-ps4-pro/ https://www.techadvisor.co.uk/news/game/google-stadia-news-3693903/

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[Originally posted on 11/06/18]

 

Today in San Francisco, California, AMD held a special event where we announced the newest additions to the Radeon Instinct™ family of compute products. The AMD Radeon Instinct™ MI60 and Radeon Instinct™ MI50 accelerators are the first GPUs in the world that are based on the advanced 7nm FinFET process technology. The ability to go down to 7nm allows us to put more transistors on to an even smaller package than was possible before – in this case, the MI60 contains 13.2 billion transistors on a package size of 331.46mm2, while the previous generation Radeon Instinct™ MI25 had 12.5 billion transistors on a package size of 494.8mm2 – a 58% improvement in number of transistors per mm2. This allows us to provide a more powerful and robust product, capable of tackling a wide range of workloads from training and inference, to high performance computing.

 

 

Supercharged Deep Learning Operations – Ideal for Training and Inference

 

We’ve made numerous improvements on these new products, including optimized deep learning operations. In addition to native half-precision (FP16) performance, the MI60 and MI50 now support INT8 and INT4 operations, delivering up to a whopping 118 TFLOPS of INT4 peak performance on the MI60. The supercharged compute capabilities of these new products are designed to meet today’s demanding system requirements of handling large data efficiently for training complex neural networks and running inference against those neural networks used in deep learning.

 

Vega20_LBlue_JPEG-768x432.jpg

 

World’s Fastest Double Precision PCIe® Based Accelerator

 

On the other end of the compute spectrum are FP64 calculations primarily used in high performance compute workloads. These types of workloads require extreme accuracy and speed, which the MI60 and MI50 deliver. The Radeon Instinct MI60 is the fastest double precision PCIe® based accelerator1, delivering up to 7.4 TFLOPS of FP64 peak performance, while the MI50 is not far behind at 6.7 TFLOPS. In addition to fast FP64 performance, the MI60 and MI50 both sport full-chip ECC memory3 as well as RAS4. This allows scientists and researchers across several industries including life sciences, energy, automotive and aerospace, government and more to achieve results with both speed and accuracy.

 

RadeonInstinct_FrontAngle_RGB_5inch-768x679.png

Finely Balanced, Ultra-Scalable Datacenter Solution

 

Most of the improvements we’ve talked about so far have been at the chip level, but we didn’t stop there. We also have a number of new benefits found beyond the chip as well. We meticulously designed the MI60 and MI50 to deliver finely tuned and balanced performance. We took a look at some of the common bottlenecks found in previous generations and made improvements to ensure your data is processed in the most efficient manner possible. This includes making these cards PCIe® Gen 4* capable, delivering up to 2x more bandwidth (64 GB/s vs. 32 GB/s) than PCIe® Gen 3 when communicating over the bus. In addition to improved performance between GPU and CPU, we’ve also built in to these products a peer-to-peer GPU communication feature called Infinity Fabric™ Link technology. Each card includes two physical Infinity Fabric™ Links allowing you to directly connect four GPUs together in a GPU hive ring and up to two of these hives in an 8 GPU server. Each GPU card provides up to 200 GB/s bandwidth between peer GPUs, which is up to 6x faster than PCIe Gen 3 alone2. We have also doubled memory bandwidth speeds from our previous generation Radeon Instinct MI25 accelerator5, delivering up to 1TB/s memory bandwidth on both the MI50 and MI60 accelerator – the first GPUs to achieve this speed.

 

RadeonInstinct_MI60_Multi4_Ang1_RGB_5inch-768x638.png

 

With improved performance from both within the GPU and between GPUs and CPUs, these new finely-balanced, ultra-fast and scalable solutions are the ideal datacenter compute solution for all your needs whether they’re inference, training or HPC related.

 

Learn More About the AMD Radeon Instinct MI60

Learn More About the AMD Radeon Instinct MI50

Learn More About AMD’s “Vega 7nm” Technology

Learn More About ROCm

 

 

Warren Eng is a Product Marketing Manager for professional graphics and compute at AMD. His postings are his own opinions and may not represent AMD’s positions, strategies or opinions. Links to third party sites are provided for convenience and unless explicitly stated, AMD is not responsible for the contents of such linked sites and no endorsement is implied. GD-5

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[Originally posted on 11/21/17]

 

This year at SC17, AMD showcased Radeon Instinct™ accelerators, AMD EPYC™ processors and the ROCm open software platform – a complete ecosystem to drive a new era in the datacenter. Our booth was packed with server racks from partners like Inventec, Gigabyte, Supermicro and BOXX. Attendees had the opportunity to check out Project 47, both on display and running demos, offering 1 PetaFLOPS of compute power.

 

The much anticipated TensorFlow support with ROCm 1.7 was revealed in our booth alongside a demo of deep learning inference from a trained Caffe model. AMD also offered hourly Tech Talks, diving into a wide range of topics – from AMD EPYC™ performance to Radeon technology powering the exploration of dark energy with the CHIME radio telescope.

 

Thank you to everyone that joined us at SC17. For those that were unable to attend, check out our photo gallery below. We hope to see you next year at SC18!

 

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Daniel Skrba, Marketing and Communications Specialist for the Radeon Technologies Group at AMD. His postings are his own opinions and may not represent AMD’s positions, strategies, or opinions. Links to third party sites and references to third party trademarks are provided for convenience and illustrative purposes only. Unless explicitly stated, AMD is not responsible for the contents of such links, and no third party endorsement of AMD or any of its products is implied.

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[Originally posted on 10/27/17]

 

Visit AMD at our SC17 booth #825 and learn how AMD together with our partners is bringing about a new era in the datacenter that is revolutionizing High Performance Computing with our new AMD EPYC™ processors and Radeon Instinct™ accelerators. On top of this year’s show stopping demos, you will have the opportunity to attend one of our interactive and educational booth Tech Talks – check out the schedule below.

 

Featured AMD Tech Talks

 

Tuesday, Nov. 14th, 2017

 

  • 11AM: Reconfigurable Acceleration at Cloud Scale, Manish Muthal, Vice President of Data Center Marketing, Xilinx
  • 1PM: Introducing AMD EPYC™: A New Standard of Performance and Innovation, Girish Kulkarni, Director of Product Marketing, AMD Server Group, AMD
  • 2PM: Exploring Dark Energy with the CHIME Radio Telescope, powered by Radeon™ Technology, Andre Renard, Chime Computing Specialist, Dunlap institute for Astronomy & Astrophysics, University of Toronto
  • 3PM: AMD EPYC™ for HPC, Joshua Mora, PhD, Manager Field Application Engineering, AMD
  • 4PM: AMD Radeon Instinct™ Accelerators, Niles Burbank, Sr. Product Manager, AMD
  • 5PM Redefining HPC Performance with EPYC-based Supermicro Servers, Super Micro Computer, Inc.

 

Wednesday, Nov. 15th, 2017

 

  • 11AM: Interconnect Your Future with Mellanox “Smart” Interconnect, Gilad Shainer, Vice president of Marketing, Mellanox Technologies
  • 1:00 PM: Accelerating 3D Acoustics With HCC-C++, Reid Atcheson, Accelerator Software Engineer, NAG
  • 2PM: AMD EPYC™ for HPC, Joshua Mora, PhD, Manager Field Application Engineering, AMD
  • 3PM: Advances in GPU Networking at AMD, Michael Lebeane, Sr. Design Engineer, AMD Research
  • 4PM: Running TensorFlow on AMD’s ROCm software platform with HIP, Ben Sander, Sr. Fellow, Software Engineer, AMD
  • AMD Booth # 825 Tech Talks November 14 – 15, 2017

 

Venue: COLORADO CONVENTION CENTER (Denver, CO)

 

We hope to see you in Denver!

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[Originally posted on 10/10/17 - by Gregory Stoner]

 

AMD is excited to see the emergence of the Open Neural Network Exchange (ONNX) format which is creating a common format model to bridge three industry-leading deep learning frameworks (PyTorch, Caffe2, and Cognitive Toolkit) to give our customers simpler paths to explore their networks via rich framework interoperability.

 

The ONNX format, via its extensible computation graph model, built-in operators, and standard data types will allow our team to focus on more in-depth optimization with our Radeon Instinct Hardware and more productive solution set via our open source MIOpen deep learning solver library and ROCm Compiler technology. It also gives us the path to explore new foundation production beyond traditional frameworks for production to bring lighter weight more optimized solutions for our hardware.

 

It is great to see the collaboration of Facebook and Microsoft continuing to also follow in the path of open software development practice with ONNX, building on their open source projects PyTorch, Caffe2, and Cognitive Toolkit. Open Software development aligns with our philosophy of bringing out open source software platform, tools, and driver to allow the research community to have more powerful ability to explore broader deep learning design space.

 

We feel this is an excellent step for the community to open up these platform to a broader set of diverse architectures. We look forward to working with the project and help it grow in the coming months.

 

 

Gregory Stoner, is Sr. Director of Radeon Open Compute. Links to third-party sites and references to third-party trademarks are provided for convenience and illustrative purposes only. Unless explicitly stated, AMD is not responsible for the contents of such links, and no third-party endorsement of AMD or any of its products is implied. Use of third-party names or marks is for informational purposes only and no endorsement of or by AMD is intended or implied.