#Teradici pcoip wddm driver
#Teradici pcoip wddm software
#Teradici pcoip wddm code

The current protocol (HDX, PCoIP or Blast) remoted FPS as well as the protocol latency. The protocol graph will be show in physical or virtual environments where a remote session is detected. Within the utilization graphs, you may zoom in or out using the left mouse button or scroll using the right mouse button, scroll wheel or page up/down keys.Ĭontrol + scroll wheel will zoom into or out of the center of the graph. The process utilization information is not serialized in the GPD file. The elements shown are GPU, GPU Memory Controller, encoder and decoder utilization. Process that do not have user query permission will not be displayed but will be part of the TOTAL utilization. While collecting data, the current process that are using the GPU are displayed in the process utilization list. The current release version does not have Network support enabled and is always disabled. If a metric does not have data in a loaded file the checkbox will be disabled. The hotkey B will allow all lines to be bolded in three steps. Selecting the checkbox will hide or show the selected counter utilization. The display options will show or hide selected metrics.Įach metric has it’s own hotkey bindings, the first press will bold the line and the second keypress will hide the metric.Ĭ for CPU, R for RAM, G for GPU, F for Framebuffer, E for Video Encode, D for Video Decode and P for Protocol metrics. The save button will allow the current data to be saved in GPD format and the export button will export to a CSV file. New will delete the current data an allow you to start collecting again. While monitoring, you can stop the monitor mode and save that in GPD format as well. The monitor button allows for continuous monitoring of a 5 minute interval. Collection OptionsĬollection options include the sample interval and duration when used with the “start” button.

#Teradici pcoip wddm driver

If detected, the NVIDIA GPU model or vGPU type, driver mode (WDDM or TCC), GPU memory and for physical machines the GPU VBIOS information.įinally the GPU driver version and hypervisor agent version. Next is the CPU model, number of logical cores and frequency as well as the system memory. The host name of the machine and the OS and build number. For physical machines it will collect the manufacturer, Model and BIOS information. In this example we have a virtual machine that is running on VMWare vSphere.

It has in my opinion become invaluable in sizing for vGPU environments and for troubleshooting both physical and virtual environments. The tool was to be small, easy to run, collect, save and ultimately share with our partners. However remoting protocol vendors only provide protocol metrics via WMI, therefore to enable capture of selected protocol metrics I am now using WMI when a native query is not available. I initially attempted to stay away from using WMI based counters due to additional overhead incurred. When an NVIDIA GPU is not detected, all other metrics can be collected for comparing CPU only and GPU workloads. These include: CPU type, number of logical cores, frequency, system memory, OS, GPU and driver version.Ī small number of metrics using native calls or the NVIDIA APIs NVAPI or NVML were used to minimize measurement impact. I included capturing many of the important system details to correlate utilization information within a sea of desktop, workstation and server hardware.

#Teradici pcoip wddm code

GPUProfiler is not a source code profiler but a resource and utilization profile that can provide a snapshot of a system and select resource utilization metrics over a period of time.

#Teradici pcoip wddm software

I needed a small tool to understand existing system configuration and performance metrics that impact the sizing decision making process.Īfter several years of attempting to extract configuration information, utilization metrics and software configuration information from partners or customers, I realized that having a small tool that could be easily shared with partners and customers to help understand what resources are being highly utilized and the context of that utilization information. GPUProfiler was created to accelerate analysis of resource utilization within physical environments to allow for better resource sizing for virtual GPU environments and troubleshoot performance issues. It is provided as a binary-only Freeware closed source project. GPUProfiler is not an NVIDIA product, nor is it supported or endorsed by NVIDIA. I am an NVIDIA employee however GPUProfiler has been developed and released independently of my employment at NVIDIA. The first release of GPUProfiler for Linux v1.07b can be found on the GPUProfiler for Linux project page All Releases The latest release of GPUProfiler is v1.07a3 on 06-27-2021