TensorFlow and CPU - tensorflow

I got the message "The TensorFlow library wasn't compiled to use SSE instructions...etc"
According to some answers in StackOverflow, this type of message, is coming up when "old" computers are used. All hints and suggestions related to installing TensorFlow did not work for me. My PCs are ca. 8-10 years old.
My question: What minimum configuration of a NEW PC (e.g. Intel, NVIDIA with GPU graphic card) is supposed to be used in order to make TensorFlow installed/working? Is any newer PC and/or notebook appropriate, independently of the Manufacturer?
I use OS Ubuntu 20.04, eventually Windows in rare cases.
Thank you
Bruno

The minimum system and software requirement to work with tensorflow was
System requirements
Ubuntu 16.04 or higher (64-bit)
macOS 10.12.6 (Sierra) or higher (64-bit) (no GPU support)
Windows Native - Windows 7 or higher (64-bit)
Windows WSL2 - Windows 10 19044 or higher (64-bit)
Software requirements
Python 3.7–3.10
pip version 19.0 or higher for Linux (requires manylinux2010 support) and Windows. pip version 20.3 or higher for macOS.
For, more details please refer to this documentation. Thank You.

Related

How to deal with CUDA version?

How to set up different versions of CUDA in one OS?
Here is my problem: Lastest Tensorflow with GPU support requires CUDA 11.2, whereas Pytorch works with 11.3. So what is the solution to install both libraries in Windows and Ubuntu?
One solution is to use Docker Container Environment, which would only need the Nvidia Driver to be of version XYZ.AB; in this way, you can use both PyTorch and TensorFlow versions.
A very good starting point for your problem would be this one(ML-WORKSPACE) : https://github.com/ml-tooling/ml-workspace

Is there a way to run RAPIDS on windows pc?

I am trying to run Nvidia rapids on a windows computer but haven't had any luck. I have installed docker desktop for windows and downloaded the rapids image. Cuda 10.0 is installed, and Nvidia-container-toolkit isn't. I haven't been able to make it run. Any thoughts or guidance?
I'm not sure if anyone has given a more definite 'updated' answer to the original question. At this point (August 2020) the answer is "Yes!". You definitely can run RAPIDS in WSL2 on Windows 10 subject to a few conditions:
Requirements
You must use RAPIDS in the Windows Subsystem for Linux version 2 (WSL2);
Windows 10 Version
2004 (OS Build 202001.1000 or later)
You have to sign up to get Windows Insider Preview versions, specifically the Developer Channel. This is required for the WSL2 VM to have GPU access. https://insider.windows.com/en-us/
CUDA version 455.41 in CUDA SDK v11.1
You must be using a special version of the NVIDA CUDA drivers (I'm using )
that you must get by a special download from NVIDIA's site. You must
join the NVIDIA Developer Program to get access to the version
-- then search for 'WSL2 CUDA Driver' and it should lead you to it.
Setup
Install the developer preview version of windows. Make sure to click the check box in 'update' that installs other recommended updates too.
Install the windows CUDA driver from the NVIDIA Developer Program
Enable WSL 2 by enabling the "Virtual Machine Platform" optional feature. You can find more steps here https://learn.microsoft.com/en-us/windows/wsl/install-win10
Install WSL from the Windows Store (Ubuntu-20.04 confirmed working)
Install python on the WSL VM, tested with Anaconda
Install Rapids AI (It's best to install this right now before you have hundreds of other packages for 'conda' to try to self-consistently reconcile with the rapids dependency graphs -- you can always install additional python packages via pip or conda later.)
After doing this, if you launch ipython...
Python 3.8.3 (default, May 19 2020, 18:47:26)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.17.0 -- An enhanced Interactive Python. Type '?' for help.
>>> import cuml
>>> cuml.__version__
'0.15.0'
>>> import cudf
>>> cudf.__version__
'0.15.0'
>>> import dask_cudf
>>> dask_cudf.__version__
'0.15.0'
>>> import cupy
>>> cupy.__version__
'7.8.0'
...and you're good to go with RAPIDS AI.
Update 9/6/20: The answer written by Wesley is accurate with the latest Windows Insider Preview with WSL2. Rather than revising this answer, I've just made the edits to his. https://stackoverflow.com/a/59364773/6779504
No. As it exists now, RAPIDS requires a Linux host. This came up in a recent workshop by NVIDIA. It was also mentioned that RAPIDS won't work with WSL. It may work with WSL version 2, but I haven't tried it nor am aware of someone that as.
The only option would if you could assign a GPU to a Linux VM on the Windows host. This possible but sufficiently complex that dual-booting is a better solution.

Will CUDA10 + CUDNN + tensorflow work on Ubuntu14.04?

It is now Oct 29, 2018
After much googling, I have not found a definitive answer or any examples of people using the latest cuda10 for tensorflow on ubuntu 14.04.
My dilemma is whether to upgrade my OS (currently at 14.04) in order to run cuda9 so I can use the latest tensorflow version or use CUDA10 on my existing 14.04 install.
Note cuda9 does not support 14.04, however, Nvidia has indicated that 14.04 will be supported for cuda10.
So, any examples/experiences of people using tensorflow with cuda10 on ubuntu14.04 are keenly sought after!
Also note cuda10 is not specifically supported by tensorflow...yet...they say "soon". But TF can be built from source with cuda10.
This is a link for cuda10+tensorflow on ubuntu16.04:
https://github.com/tensorflow/tensorflow/issues/22706
The short answer, I realize, is "try building it myself". Before I do that, I thought I'd ask around. Thanks.
I don't know whether CUDA 10 can work well on Ubuntu 14.04, but I was managed to build TensorFlow with CUDA 10 on Ubuntu 18.04 with using NVIDIA released docker image.
You can pull the 'TensorFlow Release 18.09' and try it on your current system.
If the previous step does not work, consider upgrading your OS to 18.04.
I wrote down my installation experience on this page, you could read it for some detail if you need.

Using VMWare Fusion to access GPUs

I am running the VM Fusion 8 Pro with Ubuntu 14.04 on a MacPro. The MacPro comes with dual AMD FirePro D500 GPUs. I installed the AMD APP SDK within Ubuntu, but it is only seeing the CPU as a device, and not the GPUs. Can someone please guide me so that I can run OpenCL kernels on the GPU(s).
Googling has revealed things like GPU passthrough, but there isn't enough detail on how to exactly access a GPU from within VMWare Fusion.
Sincerely,
Vishal
Last time I checked it was necessary to have motherboard support to allow the virtual machines to access the GPUs.

problems installing a virtual machine

I am tryin to install kali linux 1.0.9 on virtualbox for some testing purposes. (I am new with virtual machines). So i downloaded the 64-bit version of the os. i have got two problems:-
for some reason virtualbox does not show me a debian 64 bit version option in the settings(however it does show 32-bit option).
virtualbox doesnt allow me to change the no. of processors(default value is 1). i have got 8 cpus.
please help. my specs - intel i7 2670 memory- 6GB HDD-700 GB graphics - radeon 7670 HD
I have got windows 7 ultimate 64-Bit installed on the host
You need to enable 'Virtualization' option in your BIOS settings. The name of the settings may be different in different BIOS/motherboard brands. But you can easily identify it, in the BIOS.
I also had the same problem. I am in windows 8.1 and for my case, the problem was due to conflicts with Hyper-V who was activated in my system. I solved the problem by disabling Hyper-V.
Open windows features and Uncheck Hyper-V, click/tap on OK