A library of array-based linear algebra solvers for LabVIEW FPGA designed for ease of use over efficiency or timing.
The provided palette has functions for
- Matrix-matrix multiply
- Vector-matrix multiply
- Matrix-vector multiply
- Dot-product
- Matrix inverse
- Matrix transpose
- Cholesky Decomposition
- Eigenvalue
All functions except the eigenvalue are polymorphic and can take both single precisions floating data type and fixed-point data points up to a word length of 12 and integer word length of 32. Note that the eigenvalue function only supports single precisions floating point.
These functions enable array-based deployment of algorithms to FPGAs. Arrays are stored in the look-up tables (LUT) for ease of implementation.
Click Releases on the right-hand side of the screen and download the latest release. The .vip file is what you want and is called "arts_lab_lib_array_based_linear_algebra-x.x.x.x.vip". You can install .vip files through NI's VIPM Browser.
Houses all the code used in building and developing the functions, including test deployments to FPGAs.
Houses the published packages.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Cite as:
@Misc{Downey2021LabVIEWFPGAArray,
author = {Austin Downey},
howpublished = {GitHub},
title = {Lab{VIEW} {FPGA} Array-based Linear Algebra},
year = {2021},
groups = {{ARTS-L}ab},
url = {https://github.com/ARTS-Laboratory/LabVIEW-FPGA-Array-Based-Linear-Algebra},
}