Documentation

Choose a Parallel Computing Solution

Process your data faster or scale up your big data computation using the capabilities of MATLAB^®, Parallel Computing Toolbox™ and MATLAB Parallel Server™.

Problem	Solutions	Required Products	More Information
Do you want to process your data faster?	Profile your code.	MATLAB	Profile Your Code to Improve Performance
	Vectorize your code.	MATLAB	Vectorization
	Use automatic parallel computing support in MathWorks products.	MATLAB Parallel Computing Toolbox	Run MATLAB Functions with Automatic Parallel Support
	If you have a GPU, try `gpuArray`.	MATLAB Parallel Computing Toolbox	Run MATLAB Functions on a GPU
	Use `parfor`.	MATLAB Parallel Computing Toolbox	Interactively Run a Loop in Parallel Using parfor
Are you looking for other ways to speed up your processing?	Try `parfeval`.	MATLAB Parallel Computing Toolbox	Evaluate Functions in the Background Using parfeval
Are you looking for other ways to speed up your processing?	Try `spmd`.	MATLAB Parallel Computing Toolbox	Run Single Programs on Multiple Data Sets
Do you want to scale up your big data calculation?	To work with out-of-memory data with any number of rows, use tall arrays. This workflow is well suited to data analytics and machine learning.	MATLAB	Big Data Workflow Using Tall Arrays and Datastores
	Use tall arrays in parallel on your local machine.	MATLAB Parallel Computing Toolbox	Use Tall Arrays on a Parallel Pool
	Use tall arrays in parallel on your cluster.	MATLAB Parallel Computing Toolbox MATLAB Parallel Server	Use Tall Arrays on a Spark Enabled Hadoop Cluster
	If your data is large in multiple dimensions, use `distributed` instead. This workflow is well suited to linear algebra problems.	MATLAB Parallel Computing Toolbox MATLAB Parallel Server	Run MATLAB Functions with Distributed Arrays
Do you want to offload to a cluster?	Use `batch` to run your code on clusters and clouds.	MATLAB Parallel Server	Run Batch Parallel Jobs

Related Topics

Parallel Computing Toolbox Documentation

Support