OctaneBench – Benchmark results

I use primarily Nvidia GPU cards for rendering, some ML, Cuda projects etc – and occasionally run benchmarks on the cards l have on different workstations for comparison.

Using OctaneBench – click here to download – here are some results. I used OctaneBench 4.00c

GTX970 4GB Desktop PC     94.16











GTX1060 6GB – on Alienware 17R5 Laptop   91.31










GTX 1080 8GB – Desktop PC – 147.30











Seems a bit odd to me that a GTX1060 is beat by a GTX970, but that might be because of the mobile vs desktop version? , l am pretty sure l have ran other tests posted on this website showign a GTX1060 exceeding a GTX970


QuadQuadro M600M 2GB   21.23




Machine Learning & Links

“Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a “Field of study that gives computers the ability to learn without being explicitly programmed”.” ..Wikipedia



Useful links:


The Windows SDK version 10.0.15063.0 was not found [ Nvidia Cuda GPU Sample Code Compilation]

I get the below error message snippet a lot while trying to compile Nvidia Cuda 10 samples for testing Cuda GPU development [ c++ code]:

The Windows SDK version 10.0.15063.0 was not found. Install the required version of Windows SDK or change the SDK version in the project property pages or by right-clicking the solution and selecting “Retarget solution”.
145>Done building project “topologyQuery_vs2017.vcxproj” — FAILED.

Solution l have found is to double check the Visual Studio 2017 installer and check installing below. It seems even though l have a full VS 2017 installation with all the default sections installed, a more recent SDK is installed on my workstation.

I run Windows 10 Home together with Visual Studio 2017 Enterprise Edition, and have Nvidia Cuda 10 installed for GPU programming.

After doing above, l was able to successfully compile most of the Cuda Code samples as shown below, without the previous error. Yes!!


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.