Aceleración de algoritmos mediante GPU
Para acelerar su código, puede intentar utilizar la GPU de su ordenador. Si todas las funciones que quiere utilizar son compatibles con la GPU, puede utilizar simplemente la función gpuArray para transferir los datos de entrada a la GPU y llamar a la función gather para recuperar los datos de salida de la GPU. En deep learning, MATLAB® proporciona soporte paralelo automático para varias GPU. Necesita Parallel Computing Toolbox™ para habilitar el soporte de GPU.
Para obtener una lista de las funciones que admiten arreglos de GPU, consulte Lista de funciones (arreglos de GPU).
Temas
- Run MATLAB Functions on a GPU (Parallel Computing Toolbox)
Supply a
gpuArrayargument to automatically run functions on a GPU. - GPU Computing Requirements (Parallel Computing Toolbox)
Support for NVIDIA® GPU architectures.
- Run MATLAB Functions on Multiple GPUs (Parallel Computing Toolbox)
This example shows how to run MATLAB® code on multiple GPUs in parallel, first on your local machine, then scaling up to a cluster.
- Deep Learning with MATLAB on Multiple GPUs (Deep Learning Toolbox)
Speed up deep neural network training using multiple GPUs locally or in the cloud.
- Pedestrian and Bicyclist Classification Using Deep Learning (Radar Toolbox)
Classify pedestrians and bicyclists based on their micro-Doppler characteristics using deep learning and time-frequency analysis. (Desde R2021a)
- GPU Acceleration of Scalograms for Deep Learning (Wavelet Toolbox)
Use your GPU to accelerate feature extraction for signal classification.
Información relacionada
Ejemplos destacados
Accelerate Correlation with GPUs
Use a graphics processing unit to accelerate cross-correlation in applications that involve large data sets.
Accelerate Signal Feature Extraction and Classification Using a GPU
Use a graphical processing unit (GPU) to extract signal multidomain features for bearing fault detection.
Classify ECG Signals Using Long Short-Term Memory Networks with GPU Acceleration
Classify heartbeat electrocardiogram data using deep learning and signal processing with GPU acceleration.
Waveform Segmentation Using Deep Learning
Segment human electrocardiogram signals using time-frequency analysis and deep learning.
Human Health Monitoring Using Continuous Wave Radar and Deep Learning
Use a deep learning network to reconstruct electrocardiograms from continuous-wave radar signals.
