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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 Distributed Computing Server™.

ProblemSolutionsRequired ProductsMore Information
Do you want to process your data faster?Profile your code.MATLABProfile to Improve Performance (MATLAB)
Vectorize your code.MATLABVectorization (MATLAB)
Use built-in parallel computing support in MathWorks products.

MATLAB

Parallel Computing Toolbox

Built-in Parallel Computing Support
If you have a GPU, try gpuArray.

MATLAB

Parallel Computing Toolbox

Identify and Select a GPU Device
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
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 Distributed Computing 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 Distributed Computing Server

Distributing Arrays

Do you want to offload to a cluster? Use batch to run your code on clusters and clouds.

MATLAB Distributed Computing Server

Run Batch Parallel Jobs

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