I'm trying to run my Nvidia GPU in Hyper-V guest machine. I read that this can be done with RemoteFX from Hyper-V settings. The problem is that when I try to add my GPU to RemoteFX it say "this gpu does not meet the minimum requirements for RemoteFX". The only option, that can be chosen is my Intel GPU. So can someone tell what are the minmum requirements and why my Intel GPU can be used, but Nvidia GPU cannot?
I'm using windows 10 Enterprise, with GPU Nvidia GTX 850M and Intel i5 4200H with Intel HD Graphics 4600. My DirectX version is 12 and Driver model: WDDM 2.0.
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I am setting up my computer for two things:
Rendering with Blender
Machine learning training
I have the NVIDIA GeForce RTX 2080 but when I start the rendering in Blender it only uses the Intel UHD Graphics card, and less than 10 percent of it (according to the Task Manager). (Also, when I use Tensorflow the GPU is not detected either.). What should I do to properly set up the NVIDIA GPU to be seen by Blender (or even Tensorflow)?
Details:
Driver: NVIDIA driver version 461.72
Platform: Windows 10 Education version 1909 Build 18363.1379
Processor: Intel(R) Core(TM) i7-9700K CPU #3.6GHz 3.6GHz
GPU 0 : Intel UHD Graphics 630
GPU 1 (shown as GPU 2 in Task Manager): NVIDIA GeForce RTX 2080
Image showing the Task Manager
Image showing second GPU information
For setting the main gpu for blender, first go to settings and then go to the display section in the system category , scroll down click on graphics settings . If you have installed blender from the Microsoft store change the desktop app selection in add an app and change it to Micrsoft store app and choose blender then click on options change the gpu to the RTX 2080. If you have installed using an exe or an msi file you can click on the browse button and go to the blender install path and select the app's exe file, then click on options and change the gpu
I know Quadro 2000 is CUDA 2.1.
My PC specs as follows:
Quadro 2000 with 16GB RAM.
Xeon(R) CPU W3520 #2.67GHz 2.66GHz
Windows 10Pro.
I want to use Tenserflow for Machine Learning, and Deep Learning.
Let me know a little in-depth, as I am a beginner.
Your system is eligible to use TensorFlow but not with GPU because that requires GPU a having compute capability more than 3.0, and your GPU is only a compute capability 2.1 device.
You can read more about it here.
If you want to use GPU for training you can use some free resource available on the internet
colab - https://colab.research.google.com/
kaggle - https://www.kaggle.com/
google GCP - https://cloud.google.com/ - get free 300$ resource for 1 year validity
My Operating System is Windows 10 and I am using Keras with Tensorflow backend on CPU. I want to buy the "Nvidia Titan x (Pascal)" GPU as it is recommended for tensorflow on Nvidia website:
http://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-configurations.html
They recommend Ubuntu 14.04 as the OS.
Does anybody know if I can use Tensorflow on Nvidia Titan x (Pascal) GPU, on my Windows 10 machine?
Thanks a lot.
I've tensorflow installed with CUDA 7.5 and cuDNN 5.0. My graphics card is NVIDIA Geforce 820M with capability 2.1. However, I get this error.
Ignoring visible gpu device (device: 0, name: GeForce 820M, pci bus id: 0000:08:00.0) with Cuda compute capability 2.1. The minimum required Cuda capability is 3.0.
Device mapping: no known devices.
Is there any way to run GPU on a 2.1 capability?
I scoured online to find that it is cuDNN that requires this capability, so will installing an earlier version of cuDNN enable me to use GPU?
tensorflow-gpu requires GPUs of compute capability 3.0 or higher for GPU acceleration and this has been true since the very first release of tensorflow.
cuDNN has also required GPUs of compute capability 3.0 or higher since the very first release of cuDNN.
With tensorflow (using Keras), you might be able to get it to run with PlaidML PlaidML. I have been able to run tensorflow with GPU on AMD and NVidia GPUs (some are old) with PlaidML. It's not as fast as CUDA, but much faster than your CPU.
For reference, I have run it on an old Macbook Pro (2012) with an NVidia 650 GPU (1.5 GB) as well as an AMD HD Radeon 750 3GB.
The caveat is that it needs to be Keras vs lower level TF. There are lots of articles on it, and now it has support from Intel.
I bought a dell 7559 laptop for deep learning. I got ubuntu 16.04 installed on it but I am having trouble getting caffe and tensorflow on it. The laptop used Nvidia Optimus technology to switch between gpu and cpu to save battery usage. I checked the bios to see if I can set it to use only gpu but there is no option for it. Using bumblebee or nvidia-prime didnt work either. I now have ubuntu 16 with mate desktop environment it is preventing from getting the black screen but didnt help with the cuda issue. I was able to install the drivers and cuda but when I build caffe and tensorflow they fail saying that it didnt detect a gpu. And I wasnt able to install opengl. I tried using several versions of nvidia drivers but it didnt help. Any help would be great. thanks.
I think Bumblebee can enable you to run Caffe/Tensorflow in GPU mode. More generally, it also allows you to run other CUDA programs on a laptop with Optimus technology .
When you have installed Bumblebee correctly (tutorial: Bumblebee Wiki for Ubuntu ), you can invoke the Caffe binary by pepending optirun before the caffe binary. So it goes like the following:
optirun ../../caffe-master/build/tools/caffe train --solver=solver.prototxt
This works for the NVidia DIGITS server as well:
optirun ./digits-devserver
In addition, Bumblebee also works on my dual-graphics desktop PC (Intel HD 4600 + GTX 750 Ti) as well. The display on my PC is driven by the Intel HD 4600 through the HDMI port on the motherboard. The NVidia GTX 750 Ti is only used for CUDA programs.
In fact, for my desktop PC, the "nvidia-prime" (it's actually invoked through the command line program prime-select) is used to choose the GPU that drives the desktop. I have the integrated GPU connect to the display with the HDMI port and the NVidia GPU through a DisplayPort. Currently, the DisplayPort is inactive. The display signal comes from the HDMI port.
As far as I understand, PRIME does so by modifying /etc/X11/Xorg.conf to make either the Intel integrated GPU or the NVidia GPU the current display adapter available to X. I think the PRIME settings only makes sense when both GPUs are connected to some display, which means there need not be an Optimus link between the two GPUs like in a laptop (or, for a laptop with a Mux such as Dell Precision M4600, the Optimus is disabled in BIOS).
More information about the Display Mux and Optimus may be found here: Using the NVIDIA Driver with Optimus Laptops
Hope this helps!