Big data processing with matlab parallel computing and applications

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

Parallel Computing Toolbox

Parallel Computing Toolbox

Parallel Computing Toolbox

Parallel Computing Toolbox

Parallel Computing Toolbox

Parallel Computing Toolbox

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.

Use tall arrays in parallel on your local machine.

Parallel Computing Toolbox

Use tall arrays in parallel on your cluster.

Parallel Computing Toolbox

MATLAB Parallel Server

If your data is large in multiple dimensions, use distributed instead.

This workflow is well suited to linear algebra problems.

Parallel Computing Toolbox

MATLAB Parallel Server

MATLAB Parallel Server

Related Topics

• Profile Your Code to Improve Performance
• Vectorization
• Built-in Parallel Computing Support
• Identify and Select a GPU Device
• Interactively Run Loops in Parallel Using parfor
• Evaluate Functions in the Background Using parfeval
• Run Single Programs on Multiple Data Sets
• Choose Between spmd, parfor, and parfeval
• Big Data Workflow Using Tall Arrays and Datastores
• Use Tall Arrays on a Parallel Pool
• Use Tall Arrays on a Spark Cluster
• Distributing Arrays to Parallel Workers
• Run Batch Parallel Jobs