Amazon Linux AMI with NVIDIA TESLA GPU Driver
NVIDIA | 2018.03.0.20201028.0Linux/Unix, Amazon Linux 2018.03 - 64-bit Amazon Machine Image (AMI)
Couldn't get Blender running
Although I'm not a linux guru I do know how to handle the console, compile stuff etc.
I spent about 6 (payed) hours trying to get Blender running in this machine, without success.
- There's no Blender yum package
- After enabling Epel (and confirming that it's enabled) strangely there still is no Blender package
- Yum cannot resolve the dependencies of a recent Blender rpm (libGLEW etc)
- Compiling Blender there's version collisions with libgcc
- Tediously installing dependencies by hand resulted in more conflicts
Etc. pp.
I have no idea what kind of system that is and honestly I have no experience with RHEL. So some of you might laugh about me now, I'm ok with that.
But to my defense nobody on stackoverflow could answer that simple question "How to install Blender into this AMI" either.
I'm trying now my way with a generic Ubuntu image and getting CUDA and Nvidia drivers up and running there. Blender's working there, also a custom build, without issues.
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Not up-to-date and rather poor
The drivers that are shipped with this image are not particularly up-to-date, even though the image apparently has been updated recently.
Most of the nvidia stuff has been installed into /opt/nvidia, but other stuff in /usr/lib64. Which is not a problem per se, just inconstent and a minior inconvenience.
Some things are just broken for development purposes, like the CUDA pkg-config file, which returns this build bot directory as location for the includes:
$ pkg-config --cflags cuda-6.5
-I/builddir/build/BUILDROOT/cuda-6.5.14-1.12.amzn1.x86_64/opt/nvidia/cuda/include
Lots of little things like that.
Having said that, it's not totally unusable.
Drivers
Out of date drivers for this machine, not worth updating as does not work! Installed latest version and got errors.
Actualy not using GPU Instance
Hallo,
We wait 4 days for GPU Instances LIMIT Increase and we decide to build our own server with GPU for testing. So we do not have a chance to test it.
Lacking in development frameworks
I've managed to get my software up and running on this AMI, but the lack of documentation and general inaccessibility of Nvidia's SDKs made it a lot more painful than it needed to be. The actual development environment for CUDA applications was bare bones, without the "GPU Computing SDK" that for some reason is separate from the "CUDA Tools" system, and is currently impossible to download from Nvidia's site.
I ended up having to spend a lot of time ferreting out different versions of the different Nvidia downloads until I could find a set that worked well together, when I'd hoped that an official AMI would come pre-provisioned with the foundations I needed, or at least some docs on how to set them up.