GPU Acceleration

Run functions on a graphics processing unit (GPU)

To take advantage of the performance benefits offered by a modern graphics processing unit (GPU), certain Wavelet Toolbox™ functions can run on a GPU. This support requires Parallel Computing Toolbox™.

Functions

expand all

cwtContinuous 1-D wavelet transform
cwtfilterbankContinuous wavelet transform filter bank
wtContinuous wavelet transform with filter bank
wvdWigner-Ville distribution and smoothed pseudo Wigner-Ville distribution
fftFast Fourier transform
ifftInverse fast Fourier transform
fft22-D fast Fourier transform
ifft22-D inverse fast Fourier transform
fftshiftShift zero-frequency component to center of spectrum
ifftshiftInverse zero-frequency shift
convConvolution and polynomial multiplication
conv22-D convolution
filter1-D digital filter
filter22-D digital filter

Topics

Run MATLAB Functions on a GPU (Parallel Computing Toolbox)

Hundreds of functions in MATLAB® and other toolboxes run automatically on a GPU if you supply a gpuArray argument.

GPU Support by Release (Parallel Computing Toolbox)

Support for NVIDIA® GPU architectures by MATLAB release.

Featured Examples

GPU Acceleration of Scalograms for Deep Learning

GPU Acceleration of Scalograms for Deep Learning

Accelerate scalogram computation using GPUs. The computed scalograms are used as the input features to deep convolution neural networks (CNN) for ECG and spoken digit classification.

Open Live Script
Wavelet Time Scattering with GPU Acceleration — Music Genre Classification

Wavelet Time Scattering with GPU Acceleration — Music Genre Classification

Accelerate the computation of wavelet scattering features using gpuArray and a parallelized "depth-first" version of wavelet time scattering. You must have a CUDA-enabled NVIDIA GPU with compute capability 3.0 or higher. See GPU Support by Release for details.

Open Live Script
Wavelet Time Scattering with GPU Acceleration — Spoken Digit Recognition

Wavelet Time Scattering with GPU Acceleration — Spoken Digit Recognition

Accelerate the computation of wavelet scattering features using gpuArray and a parallelized "depth-first" version of wavelet time scattering. You must have a CUDA-enabled NVIDIA GPU with compute capability 3.0 or higher. See GPU Support by Release for details. This example uses an NVIDIA Titan XP GPU with compute capability 6.1.

Open Live Script
Wavelet Toolbox Documentation
Support