Animation

Lighthouse – Flip Fluid Bender Simulation – Using Cuda w/Issues Found

Using Blender and FlipFluids Addon

This is still baking, so far 60Gb bake files and climbing at 334 out of 501 frames. Domain resolution used – 500 – ie High Quality.

Bake files grew from 55Mb [frame 1] to currently 277Mb [frame 333] !

Will update on the progress and final render.

and finally… after almost 2 days baking non stop…..

Below shows me trying to render one single frame and yet getting out of CUDA memory error.

I’m using a GTX1080 with 8Gb VRAM, on a i7 Quad core PC with 32Gb RAM

Switching to a CPU render and the results are below.

Time taken 1 hour for frame 348

Until l can find a quicker way to render each frame, by cuda which is usually faster especially since l have access to about 3000+ cuda cores collectively on my core workstation, l will give this project a rest for now.

update 9/28/2018

I tried command line blender rendering of frames 16, 348 with my 8gb gtx1080 / l  get the cuda error as the gpu ram used reached about 7gb out of the 8gb,

Currently rendering the first 200 frames as shown below.

 

Blender

Blender Open Data

I’ve used several benchmark software to compare computer hardware especially nvidia GPU cards used for cuda programming.  One good free benchmark software is Maxon CineBench    , another is Unigine Haven

 

Here are surprising results generated from the new Blender Benchmark under its Blender Open data website program.

Quick summary/my findings:

  • less render time running Linux [LinumMint] than under Windows 10 [all things turned off], same hardware
  • SSD’s help

Linux run: Workstation with GTX1080 8Gb, GTX970 4Gb, 32Gb RAM, Quad core Intel processor. No SSD

Same hardware as above but run under Windows 10

Ran on same hardware, only using the GTX1080 8Gb , under Linuxmint – impressive resuly showing in my view and from cuda/nvidia research l did that the 4Gb of the 2nd graphics card limits the performance.

 

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Home PC #2  Results below, newer PC, no SSD, 2 x GTX560Ti

Below results from Alienware 17 [4 years old] with Samsung Evo 500Gb SSD, GTX860M

Computer Hardware

Linuxmint 18.1 – Cuda 9.1 Toolkit

Updating to the latest cuda development toolkit on Linuxmint 18.1 [with a GTX 1080+970]

Notes:

Reference links:

First, update to R390 Driver

Terminal commands

sudo dpkg -i cuda-repo-ubuntu1704-9-1-local_9.1.85-1_amd64.deb

sudo apt-key add /var/cuda-repo-9-1-local/7fa2af80.pub

sudo apt-get update

sudo apt-get install cuda

Screenshots

Animation

NVIDIA CUDA 8 with LinuxMint

Notes, screenshots and results using, installing, testing Nvidia Cuda on Linuxmint 18.1

“CUDA is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).

References:

Additional Notes:

sudo add-apt-repository ppa:maarten-baert/simplescreenrecorder
sudo apt-get update
sudo apt-get install simplescreenrecorder

 

Tests done on my custom built Workstation PC as well as Alienware 17 laptop – all GPU specs below.

Quick comparisons [not the focus of this post]  :):

  • Puget systems laptop, with a GTX 980M 8Gb  – 91 billion int./sec, 1819 Gflops
  • My Alienware 17 with a GTX 860M 2Gb – 43.3 b.i.p.s, 866 Gflops
  • My workstation with a GTX 970 4Gb -> 146 b.i.p.s, 2919 GFlops.

Screenshots in no particular order.

 

Below result from Puget Systems test on their laptop, for comparison

Below my results