DELIVERING HIGH-PERFORMANCE REMOTE GRAPHICS WITH NVIDIA GRID VIRTUAL GPU. Andy Currid NVIDIA

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1 DELIVERING HIGH-PERFORMANCE REMOTE GRAPHICS WITH NVIDIA GRID VIRTUAL Andy Currid NVIDIA

2 WHAT YOU LL LEARN IN THIS SESSION NVIDIA's GRID Virtual Architecture What it is and how it works Using GRID Virtual on Citrix XenServer How to deliver great remote graphics from GRID Virtual

3 WHY VIRTUALIZE? ENGINEER / DESIGNER Workstation POWER USER High-end PC KNOWLEDGE WORKER Entry-level PC

4 WHY VIRTUALIZE? Awesome performance! High cost Hard to fully utilize, limited mobility Challenging to manage Desktop workstation Quadro Data security can be a problem

5 CENTRALIZE THE WORKSTATION Awesome performance! Easier to fully utilize, manage and secure Even more expensive! Datacenter Desktop workstation Quadro Remote Graphics Notebook or thin client

6 VIRTUALIZE THE WORKSTATION Datacenter -enabled server Virtual Machine Guest OS Apps Virtual Machine Guest OS Apps Notebook or thin client Citrix XenServer VMware ESX Red Hypervisor Hat Enterprise Linux Open source Xen, KVM NVIDIA Driver Direct access from guest VM NVIDIA Driver Remote Graphics Dedicated per user NVIDIA GRID

7 SHARE THE Datacenter -enabled server Hypervisor Virtual Machine Guest OS Apps Virtual Machine Guest OS Apps Notebook or thin client GRID Virtual Manager NVIDIA Driver NVIDIA Driver Hypervisor Physical Management Direct access from guest VMs Remote Graphics NVIDIA GRID v

8 NVIDIA GRID VIRTUAL Standard NVIDIA driver stack in each guest VM -enabled server VM 1 VM 2 API compatibility Hypervisor GRID Virtual Manager Guest OS Apps NVIDIA Driver Guest OS Apps NVIDIA Driver Direct hardware access from the guest Hypervisor Highest performance NVIDIA GRID v GRID Virtual Manager Increased manageability

9 VIRTUAL RESOURCE SHARING -enabled server Hypervisor GRID Virtual Manager Hypervisor NVIDIA GRID v CPU MMU Channels Timeshared Scheduling 3D CE NVENC NVDEC VM 1 Guest OS Apps NVIDIA Driver VM 2 Guest OS Apps NVIDIA Driver BAR VM1 BAR VM2 BAR Framebuffer VM1 FB VM2 FB Frame buffer Allocated at VM startup Channels Used to post work to the VM accesses its channels via Base Address Register (BAR), isolated by CPU s Memory Management Unit (MMU) Engines Timeshared among VMs, like multiple contexts on single OS

10 VIRTUAL ISOLATION -enabled server MMU controls access from engines to framebuffer and system memory VM 1 VM 2 Hypervisor GRID Virtual Manager Guest OS Apps NVIDIA Driver Guest OS Apps NVIDIA Driver v Manager maintains per-vm pagetables in s framebuffer Hypervisor NVIDIA GRID v MMU Untranslated accesses 3D CE NVENC NVDEC Translated DMA access to VM physical memory and FB Framebuffer Pagetable access VM1 FB VM2 FB VM1 pagetables VM2 pagetables Valid accesses are routed to framebuffer or system memory Invalid accesses are blocked

11 NVIDIA GRID V ON CITRIX XENSERVER XenServer First hypervisor to support GRID v Also supports passthrough Open source Full tools integration for GRID certified server platforms

12 XENSERVER SETUP Install XenServer

13 XENSERVER SETUP Install XenServer Install XenCenter management GUI on PC Install GRID Virtual Manager rpm -i NVIDIA-vgx-xenserver i386.rpm

14 ASSIGNING A V TO A VIRTUAL MACHINE Citrix XenCenter management GUI Assignment of virtual, or passthrough of dedicated

15 BOOT, INSTALL OF NVIDIA DRIVERS VM s console accessed through XenCenter Install NVIDIA guest v driver

16 V OPERATION NVIDIA driver now loaded, v is fully operational Verify with NVIDIA control panel

17 DELIVERING GREAT REMOTE GRAPHICS Use a high performance remote graphics stack Tune the platform for best graphics performance

18 NVIDIA GRID SDK Apps Apps Apps Remote Graphics Stack Network Available on v and passthrough Graphics commands H.264 or raw streams Fast readback of desktop or individual render targets GRID or v 3D NVIFR NVENC NVFBC Hardware H.264 encoder Citrix XenDesktop Render Target Front Buffer VMware View NICE DCV Framebuffer HP RGS

19 TUNING THE PLATFORM Platform basics selection NUMA considerations

20 PLATFORM BASICS Use sufficient CPU! Graphically intensive apps typically need multiple cores Ensure CPUs can reach their highest clock speeds Enable extended P-states / TurboBoost in the system BIOS Set XenServer s frequency governor to performance mode xenpm set-scaling-governor performance /opt/xensource/libexec/xen-cmdline --set-xen cpufreq=xen:performance Use sufficient RAM! - don t overcommit memory Fast storage subsystem - local SSD or fast NAS / SAN

21 MEASURING UTILIZATION nvidia-smi command line utility Reports utilization, memory usage, temperature, and much more ~]# nvidia-smi Mon Mar 24 09:56: NVIDIA-SMI Driver Version: Name Persistence-M Bus-Id Disp.A Volatile Uncorr. ECC Fan Temp Perf Pwr:Usage/Cap Memory-Usage -Util Compute M. ===============================+======================+====================== 0 GRID K1 On 0000:04:00.0 Off N/A N/A 31C P0 20W / 31W 530MiB / 4095MiB 61% Default GRID K1 On 0000:05:00.0 Off N/A N/A 29C P0 19W / 31W 270MiB / 4095MiB 46% Default GRID K1 On 0000:06:00.0 Off N/A N/A 26C P0 15W / 31W 270MiB / 4095MiB 7% Default GRID K1 On 0000:07:00.0 Off N/A N/A 28C P0 19W / 31W 270MiB / 4095MiB 46% Default GRID K1 On 0000:86:00.0 Off N/A N/A 26C P0 19W / 31W 270MiB / 4095MiB 45% Default GRID K1 On 0000:87:00.0 Off N/A N/A 27C P0 15W / 31W 10MiB / 4095MiB 0% Default GRID K1 On 0000:88:00.0 Off N/A N/A 33C P0 19W / 31W 270MiB / 4095MiB 53% Default GRID K1 On 0000:89:00.0 Off N/A N/A 32C P0 19W / 31W 270MiB / 4095MiB 46% Default

22 MEASURING UTILIZATION utilization graph in XenCenter

23 PICK THE RIGHT GRID ENGINEER / DESIGNER GRID K2 2 high-end Kepler s 3072 CUDA cores (1536 / ) 8GB GDDR5 (4GB / ) POWER USER GRID K1 4 entry Kepler s 768 CUDA cores (192 / ) 16GB DDR3 (4GB / ) KNOWLEDGE WORKER

24 SELECT THE RIGHT V GRID K260Q 2GB framebuffer 4 heads, 2560x1600 ENGINEER DESIGNER GRID K2 2 high-end Kepler s 3072 CUDA cores (1536 / ) 8GB GDDR5 (4GB / ) GRID K240Q 1GB framebuffer 2 heads, 2560x1600 POWER USER GRID K MB framebuffer 2 heads, 1920x1200 KNOWLEDGE WORKER

25 SELECT THE RIGHT V GRID K260Q 2GB framebuffer 4 heads, 2560x1600 ENGINEER DESIGNER GRID K2 2 high-end Kepler s 3072 CUDA cores (1536 / ) 8GB GDDR5 (4GB / ) GRID K240Q 1GB framebuffer 2 heads, 2560x1600 POWER USER GRID K MB framebuffer 2 heads, 1920x1200 KNOWLEDGE WORKER

26 SELECT THE RIGHT V GRID K140Q 1GB framebuffer 2 heads, 2560x1600 POWER USER GRID K1 4 entry Kepler s 768 CUDA cores (192 / ) 16GB DDR3 (4GB / ) GRID K MB framebuffer 2 heads, 1920x1200 KNOWLEDGE WORKER

27 TAKE ACCOUNT OF NUMA Memory 0 Memory 1 Non-Uniform Memory Architecture CPU Socket 0 CPU Socket 1 Memory and s connected to each CPU CPU Interconnect CPUs connected via proprietary interconnect PCI Express PCI Express CPU/ access to memory on same socket is fastest Access to memory on remote socket is slower

28 PIN VCPUS TO SOCKETS CPU Socket 0 Memory 0 Virtual Machine vcpu vcpu vcpu vcpu CPU Socket 1 Memory 1 PCI Express VM pinned to CPU socket by restricting its vcpus to run only on that socket xe vm-param-set uuid=<vm-uuid> VCPUs-params:mask= 0,1,2,3,4,5

29 SELECTING A V ON A SPECIFIC SOCKET Memory 0 Memory 1 CPU Socket 0 CPU Socket 1 GRID K2 GRID K2 GRID K2 GRID K

30 GROUPS XenServer manages physical s by means of groups Group GRID K2 Allocation policy: depth first Physical s: Default behavior: all physical s of same type are placed in one group group allocation policy: Depth first: allocate v on most loaded Breadth first: allocate v on least loaded

31 GROUPS Memory 0 Memory 1 XenServer manages physical s by means of groups CPU Group Socket GRID 0 K2 Allocation policy: depth first Physical s: CPU Socket 1 Default behavior: all physical s of same type are placed in one group group allocation policy: K2 K2 K2 K2 Depth first: allocate v on most loaded Breadth first: allocate v on least loaded

32 GROUPS Memory 0 Default group takes no account of where a VM is running CPU Socket 0 Virtual Machine vcpu vcpu vcpu vcpu CPU Socket 1 Your VM may end up using a v that s allocated on a on a remote CPU socket K2

33 GROUPS Create custom groups Per socket, or per for ultimate control Group GRID K2 Socket 0 Allocation policy: breadth first Physical s: Group GRID K2 Socket 1 Allocation policy: breadth first Physical s: xe gpu-group-create name-label= "GRID K2 Socket 0 xe pgpu-param-set uuid=<pgpu-uuid> gpu-group-uuid= <group-uuid> xe gpu-group-param-set uuid=<group-uuid> allocation-algorithm= breadth-first

34 GROUPS Create custom groups Per socket, or per for ultimate control Group GRID K2 Socket 0 CPU Socket 0 Allocation policy: breadth first Physical s: GRID K2 GRID K2 Group CPU Socket GRID K2 1 Socket 1 Allocation policy: breadth first Physical s: GRID K2 GRID K2 xe gpu-group-create name-label= "GRID K2 Socket 0 xe pgpu-param-set uuid=<pgpu-uuid> gpu-group-uuid= <group-uuid> xe gpu-group-param-set uuid=<group-uuid> allocation-algorithm= breadth-first

35 WRAP UP NVIDIA's GRID Virtual Architecture GRID Virtual on Citrix XenServer Remote graphics performance

36 RESOURCES NVIDIA GRID v User Guide Included with GRID v drivers Visit look for driver download link Citrix XenServer with 3D Graphics Pack Visit Qualified server platforms Visit

37 RESOURCES Remote Graphics Citrix XenDesktop HP Remote Graphics Software (RGS) NICE Desktop Cloud Visualization (DCV) XenServer CPU performance tuning

38 THANK YOU! NVIDIA GRID Forum

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