Accelerazione dell'algoritmo GPU
Per velocizzare il codice, puoi provare a utilizzare la GPU del tuo computer. Se tutte le funzioni che desideri utilizzare sono supportate dalla GPU, puoi semplicemente utilizzare la funzione gpuArray per trasferire i dati di input alla GPU e chiamare la funzione gather per recuperare i dati di output dalla GPU. Per il Deep Learning, MATLAB® fornisce supporto parallelo automatico per più GPU. Per abilitare il supporto GPU è necessario Parallel Computing Toolbox™.
Per un elenco delle funzioni che accettano array GPU, vedere Elenco delle funzioni (array GPU).
Argomenti
- 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.
- GPU Acceleration of Scalograms for Deep Learning (Wavelet Toolbox)
Use your GPU to accelerate feature extraction for ECG and spoken digit classification.
Informazioni complementari
Esempi in primo piano
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.
