Gooseberry Benchmark 1.0 – Results – Blender 2/79b – Blender 2.8 beta

This is a CPU only render test.  Click here for the download source.

Recommended a minimum of 12 GB RAM
Creative Commons Attribution 4.0
Blender Foundation – gooseberry.blender.org

PC 1:

  • Intel i7-2600K CPU@3.4Ghz    32Gb RAM  Windows 10  GTX1080 8Gb
  • Blender 2.79b
  • Time:  1:38:20.61         1 hr 38mins

 

PC2 – A17R5:

  • Intel i7-8760H CPU@2.20Ghz  16Gb  GTX1060 6Gb Windows 10
  • Blender 2.79b
  • Time:  58 mins      58:34:08

using the latest [as of today] Blender: 2.8 beta, the CPU rendering engine time is greatly improved to:  34 minutes ! – an improvement of 24 mins !

 

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!!

Minecraft Server – STEM

I use this a lot for teaching STEM education to younger future programmers to be. The creators of mincraft had a goal of teaching and enabling, exploring  programming especially to kids, as well as having fun playing Minecraft.

Source link:  Click here.

Build instructions link here.

you also need git for windows which you can download here, as well as the latest Java JDK which you can download from here.

Screenshots:

Alienware 17 R5 – Notes

General Notes on the Dell Alienware 17 R5:

10-20-18
Base unit came with GTX1060 6gb, M.2 Sandisk 2280 128Gb, 1Tb 2.5″ Hard drive…

Quick comparison to an older unit, no dual HDD option, no DVD/Burner drive, less USB drive slots, no SD card slot, but lots of newer VR friendly options, faster CPU and faster/more current GPU

Benchmark results, see this link,

M.2 upgrade device that worked for me – in Slot 2:
WD Black M.2 2280 500Gb PCIe nvme [$129]
Note – Sandisk V-Nand will NOT work for Slot 2
Slot 3 is M.2 2240

More to come, pics, and videos

Dell Emc Windows 10 recovery usb image download link

 

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.

 

Alienware 17 R5 Benchmark

Using the software Superposition Benchmark – click here to download.

For CineBench – click here to download the free benchmark software’

Compared with my custom main workstation PC, using a dual card 8Gb GTX1080 and 4Gb GTX970

With same workstation, just with the GTX1080 8Gb card

From above, it seems my main PC as l have researched is limited a bit when a 4Gb GTX970 is in it.

Also note the processor is much older, compared to that in my new laptop below.

Below is the Alienware 17 R5 Results