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CuLab - 
GPU Accelerated Toolkit
for LabVIEW

CuLab is a very intuitive and simple to use toolkit for LabVIEW designed to accelerate computationally intensive tasks on Nvidia GPUs.


The purpose of CuLab is to provide extensive API functions to accelerate mathematical operations, BLAS (Basic Linear Algebra Subroutine) functions and common signal processing functions (FFT/IFFT) on GPUs.

The main idea of the toolkit is to provide simple mechanisms to accelerate any data processing code developed in LabVIEW on Nvidia GPUs.
 

FEATURES & FUNCTIONALITY

Easily get up to 100x ​​speed up on computationally intensive tasks in LabVIEW

FEATURE HIGHLIGHTS:
  • Minimum efforts to accelerate existing LabVIEW code on GPUs. 

  • Single step installation to start using the code (no efforts for installing additional drivers)

  • Supporting most common numeric operations and functions available in LabVIEW (more functions to be added in future releases)

  • Supporting almost all numeric types available in LabVIEW

  • Start with ready-to-run real-world example

FAMILIAR, LabVIEW-LIKE ACCELERATED CODE DEVELOPMENT
SUPPORTED FUNCTIONS
 

The toolkit supports all essential functions required to accelerate numerically intensive codes:

  • Numeric functions (add, subtract,..., datatype conversion, complex numbers)

  • Array manipulation

  • Linear algebra (BLAS1, BLAS2, BLAS3)

  • Signal processing (FFT, IFFT)

  • GPU memory management

INSTALLATION AND SYSTEM REQUIREMENTS

The toolkit comes as a VIPM (VI Package Manager) installer which includes the toolkit itself, all required drivers, documentation and reference examples

DEVELOPMENT SYSTEM REQUIREMENTS

  • LabVIEW 2020 x64 and later

  • Nvidia GTX 1xxx GPU models and newer

  • Windows 10 x64

HAVE QUESTIONS?