Cette page a été traduite par traduction automatique. Cliquez ici pour voir la dernière version en anglais.

Clusters et clouds

Découvrez les ressources du cluster et travaillez avec les profils de cluster

Si votre tâche informatique est trop volumineuse ou trop lente pour votre ordinateur local, vous pouvez transférer votre calcul vers un cluster sur site ou dans le cloud pour exécuter votre code MATLAB^® avec un minimum de modifications. Essayez Parallel > Discover Clusters dans la barre d'outils MATLAB pour savoir si vous disposez déjà d'un cluster disponible.

Si vous disposez déjà d'un cluster avec un planificateur, vous pouvez y intégrer MATLAB en utilisant MATLAB Parallel Server™. Alternativement, si vous ne disposez pas d'un planificateur existant, MATLAB Parallel Server fournit le planificateur de jobs MATLAB.

Fonctions

développer tout

Fonctions clés

`parcluster`	Créer un objet cluster
`parpool`	Créer un pool parallèle sur le cluster
`gcp`	Obtenir le pool parallèle actuel
`shutdown`	Shut down cloud cluster
`start`	Start cloud cluster
`wait (cluster)`	Wait for cloud cluster to change state
`parallel.defaultProfile`	Examine or set default cluster profile (depuis R2022b)
`parallel.exportProfile`	Export one or more profiles to file
`parallel.importProfile`	Import cluster profiles from file
`saveProfile`	Save modified cluster properties to its current profile
`saveAsProfile`	Save cluster properties to specified profile
`pctconfig`	Configure settings for Parallel Computing Toolbox client session or MATLAB Parallel Server workers

Classes

développer tout

Classes importantes

`parallel.Pool`	Pool parallèle de workers
`parallel.Cluster`	Access cluster properties and behaviors
`pctRunOnAll`	Run command on client and on all workers in parallel pool

Exemples et procédures

Configuration du cluster

Discover Clusters and Use Cluster Profiles
Find out how to work with cluster profiles and discover cloud clusters.
Scale Up from Desktop to Cluster
Develop your parallel MATLAB® code on your local machine and scale up to a cluster.
Process Big Data in the Cloud
This example shows how to access a large data set in the cloud and process it in a cloud cluster using MATLAB® capabilities for big data.
Scale Up Parallel Code to Large Clusters

Discover options to scale your parallel MATLAB code to use large HPC clusters.
Benchmark Your Cluster with the HPC Challenge
This example shows how to evaluate the performance of a compute cluster with the HPC Challenge Benchmark.

Deep Learning

Scale Up Deep Learning in Parallel, on GPUs, and in the Cloud (Deep Learning Toolbox)
Explore options for deep learning with MATLAB in parallel and using multiple GPUs, locally or in the cloud.
Deep Learning with MATLAB on Multiple GPUs (Deep Learning Toolbox)
Speed up deep neural network training using multiple GPUs locally or in the cloud.
Train Network Using Automatic Multi-GPU Support (Deep Learning Toolbox)
This example shows how to use multiple GPUs on your local machine for deep learning training using automatic parallel support.
Use parfor to Train Multiple Deep Learning Networks (Deep Learning Toolbox)
This example shows how to use a parfor loop to perform a parameter sweep on a training option.
Use parfeval to Train Multiple Deep Learning Networks (Deep Learning Toolbox)
This example shows how to use parfeval to perform a parameter sweep on the depth of the network architecture for a deep learning network and retrieve data during training.
Train Deep Learning Networks in Parallel (Deep Learning Toolbox)
This example shows how to run multiple deep learning experiments on your local machine.
Train Network in Parallel with Custom Training Loop (Deep Learning Toolbox)
This example shows how to set up a custom training loop to train a network in parallel.
Work with Deep Learning Data in AWS (Deep Learning Toolbox)
This example shows how to upload data to an Amazon S3™ bucket.
Send Deep Learning Batch Job to Cluster (Deep Learning Toolbox)
This example shows how to send deep learning training batch jobs to a cluster so that you can continue working or close MATLAB® during training.

Concepts

Spécifiez vos préférences parallèles
Spécifiez vos préférences et créez automatiquement un pool parallèle.
Set Environment Variables on Workers
Copy system environment variables from the client to workers in a cluster.

Informations connexes

Parallélisation et cloud (Deep Learning Toolbox)
Installation (MATLAB Parallel Server)
Réduisez le temps d'obtention des résultats avec MATLAB grâce au calcul parallèle

Exemples présentés

Scale Up from Desktop to Cluster

Develop your parallel MATLAB® code on your local machine and scale up to a cluster.

Ouvrir le live script

Process Big Data in the Cloud

Access a large data set in the cloud and process it in a cloud cluster using MATLAB® capabilities for big data.

Ouvrir le live script