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!!

Alienware 17 R5 – Notes

General Notes on the Dell Alienware 17 R5:

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


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.



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

Linuxmint 18.1 – Cuda 9.1 Toolkit

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


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/

sudo apt-get update

sudo apt-get install cuda


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).


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

Nvidia cuda….

Wanted to take advantage of the CUDA from NVIDIA (a leading GPU manufacturer) – a system that uses GPUs for scientific computing. You also need a minimum of 256Mb Video card RAM to take advantage of CUDA. This will also increase my BOINC/SETI processing speed. My current nvidia driver for my PNY Quadro FX370 was dated 5/26/2008 release So l downloaded the latest driver from the nvidia website and the new driver is now dated 12/26/2008 release
/this works okay on my Quad-core workstation and boosted my Vista index from 3.6 to 4.2
My Vista index ratings for my Processor/RAM/Hard drive was before and after the update 5.9
Graphics rating went from 3.6 to 4.2
Games graphics capability went from 4.0 to 4.6
It will be interesting to see this week what this GPU processing does to my boinc/seti ratings.
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