CuLab - GPU Accelerated by Ngene - Toolkit for LabVIEW Download

CuLab - GPU Accelerated Toolkit

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Version	2.1.1.50
Released	Oct 26, 2023
Publisher	Ngene
License	Ngene Custom
LabVIEW Version	LabVIEW x64>=20.0
Operating System	Windows x64
Project links	Homepage Documentation Repository

Description

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.
Almost all CuLab operation functions support all numeric data types.

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

Release Notes

2.1.1.50 (Oct 26, 2023)

V2.1.1

General Description
This version of CuLab toolkit brings new functionalities and improvements to existing ones.

New Features
1. Added Signal Operation subpalette with the following functions.
1. CU_Decimate_Single_Shot.vi
• Supports 1Ch-1Ch, MCh-1Ch, MCh-MCh modes.
• Accepts (SGL, DBL, CSG, CDB) Tensor Types.
2. CU_Rational_Resampl.vi
• Supports single channel mode.
• Accepts (SGL, DBL, CSG, CDB) Tensor Types.
3. CU_Convolution.vi
• Supports 1Ch-1Ch, MCh-1Ch, MCh-MCh modes.
• Accepts (SGL, DBL, CSG, CDB) Tensor Types.
4. Cross_Correlation.vi
• Supports single channel mode.
• Accepts (SGL, DBL, CSG, CDB) Tensor Types.
2. Added a function to the Complex subpalette.
1. CU_Interleaved_to_Complex.vi.
• Description: Converts interleaved sampled IQ data into complex representation. Designed to minimize data copy overhead during conversion.
• Supports all tensor dimensionalities except T0D.
• Accepted input datatypes (I8, U8, I16, U16, I32, U32, I64, U64, SGL, DBL)
• Supported output datatypes (CSG, CDB)
3. Added following functions to the Device Management subpalette.
1. CU_Get_GPU_List.vi
• Returns list of Nvidia GPUs available on the PC.
2. CU_Get_GPU_Properties.vi
• Returns the properties for the selected GPU ID.
3. CU_Set_GPU.vi
• Sets the selected GPU to be active.
Extended Functionalities
1. CU_Sine.vi, CU_Cosine.vi and CU_exponential.vi accept tensors with complex data representations (CSG, CDB) as input.
2. The help file was updated to reflect the updated functionalities.
Bug Fix
1. Fixed array max dimension issue in CU_Transpose_2D_Array.vi.
2. Fixed “Dest in” memory allocation issue in CU_Power_Spectrum.vi.
3. Fixed issue when CU_Square_Root.vi returned incorrect results when imaginary part is 0, and when run in in-place mode.
4. Other minor fixes.

2.0.1.39 (Feb 08, 2023)

v2.0.1

General Description
This version of CuLab toolkit brings new functionalities and improves the performance of existing ones.

Backward Compatibility
This is a major update which breaks backward compatibility with v1.0.1 version of the toolkit.

Features
1. Added Trigonometric functions:
a) Sine
b) Cosine
c) Tangent
d) Cotangent
e) Inverse Sine
f) Inverse Cosine
g) Inverse Tangent
h) Inverse Tangent 2 Input (atan2)
i) Inverse Cotangent
j) Sine & Cosine
k) Sinc

2. Added Exponential functions
a) Exponential
b) Exponential Arg -1
c) Logarithm Base 10
d) Logarithm Base 2
e) Logarithm Base X
f) Natural Logarithm
g) Natural Logarithm Arg +1
h) Power Of 10
i) Power Of 2
j) Power Of X
k) Y-th Root of X

3. Added Hyperbolic functions
a) Hyperbolic Sine
b) Hyperbolic Cosine
c) Hyperbolic Tangent
d) Hyperbolic Cotangent
e) Inverse Hyperbolic Sine
f) Inverse Hyperbolic Cosine
g) Inverse Hyperbolic Tangent
h) Inverse Hyperbolic Cotangent

4. Added missed complex APIs
a) Complex to Polar
b) Polar to Complex
c) Polar to Re/Im
d) Re/Im to Polar

5. Added function for Quotient & Remainder
6. Added support for Tensor-Constant operations for binary numeric operations
7. This allows to choose a CPU based constant as a second operand
8. Added new function generation functions
a) Ramp Pattern
b) Sine Pattern
c) Power Spectrum

9. Added support for missing numeric types for numeric operations
10. Redesigned colors for tensor wires to make them distinguishable across numeric types and dimensionality
11. Added batched versions of FFT and IFFT
12. Added spectrum shifting functionality single channel and batched FFT

Optimizations
1. Greatly improved the performance of Real-to-Complex (R2C and D2Z) FFTs
2. Optimized execution times for Complex functions
3. Other optimizations

Bug Fix
1. Fixed automatic instance selection issue in Array Max Min polymorphic function
2. Fixed memory leakage issue
3. Fixed an error in BLAS benchmarking example
4. Corrected typos
5. Other bug fixes

1.0.1.19 (Sep 07, 2022)

v 1.0.1

ngene was a contributor to this release

Show all release notes (+2 more releases)

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Versions

2.1.1.50 (Oct 26, 2023)

2.0.1.39 (Feb 08, 2023)

1.0.1.19 (Sep 07, 2022)

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Can waveform generation be included as simple trig and linear operations like ramp and sine pattern Many RF DSP maths require simple signals to perform operations. Making those signals takes horsepow… by norm!, 1 year, 7 months ago, 1 , 2
Can complex number library be fleshed out with polar transforms? Complex to polar transforms are done a TON in RF DSP. I'd love to see the impact on some core algor… by norm!, 1 year, 7 months ago, 1 , 1

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