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G2CPU GPU and CPU HPC by Natan Biesmans - Toolkit for LabVIEW Download

G2CPU GPU and CPU high performance computing toolkit

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ReleasedDec 06, 2023
Publisher Natan Biesmans
License G2CPU License Agreement
LabVIEW VersionLabVIEW x64>=20.0
Operating System Windows x64
Project links Homepage  


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G2CPU GPU and CPU high performance computing toolkit

G2CPU is a general high performance computing library for LabVIEW based on ArrayFire.
Through the same code you can dynamically choose where the computational task is executed with absolutely no hassle. Code can be run on standard CPU's, Nvidia CUDA devices and OpenCL compatible devices.

You have access to general arithmetic, array manipulation, signal processing, vector algorithms, machine vision and many more with even more to come.

Supported Technologies
When running code on you CPU the computational task is divided over multiple cores. Fully utilizing the CPU without the need for manual thread control.

Maximize your computational power on Nvidia GPU's by using Nvidia's CUDA technology.

Throug OpenCL you can run code on most commercial GPU's from all the big vendors like Intel, AMD and Nvidia. You can even run your code on the integrated graphics card on your CPU. (if available)

Intel OneAPI
The Intel OneAPI is provides its own unified acces to hardware which ranges from CPU's, GPU's to even accelerators and FPGA's. Make sure to download the latest version before using this backend.

Release Notes (Dec 06, 2023)

Machine Vision Phase 1

New Features:
- Addition of interfaces to Arrayfire image processing functions
- Addition of image processing examples
- Addition of image viewers to F32, U16 and U8 probes.
- Addition of image viewing utilities
- Addition of interfaces to Arrayfire machine vision functions

- Addition of machine vision examples
- Addition of machine vision descriptor class and phase 1 probe

- Build and Concatenate array are now robust and should not crash LabVIEW anymore
- Build and Concatenate array now have auto release behaviour similar to all other functions.
- (I)FFT's now have their default normalisation set to 1

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