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Host MATLAB Online in ICE Connect EKC. Run code on multiple Nvidia GPUs in parallel.

Requires a MATLAB license.

Helm Chart on GitLab


Install the app through Rancher.

Supported Docker images

This Helm chart can be used with MathWorks Docker images


Provides an Ubuntu-based image with an installation of MATLAB.


Also adds additional toolboxes:

  • Deep Learning Toolbox
  • Image Processing Toolbox
  • Parallel Computing Toolbox
  • More


Additional products and services

Before deploying MATLAB from Rancher, additional toolboxes can be installed from MathWorks Products and Services, such as Financial Toolbox and Optimization Toolbox.

Simulink is not supported by MATLAB Online.

SSH settings

MATLAB Online requires SSH access to the host machine. Add your SSH public key from e.g. ~/.ssh/


Requested CPU (required): The minimum number of CPU cores to request for the Jupyter server, in milli-CPU units (m). The default is 1000m, which is equivalent to one CPU core. More cores will be available freely depending on the server load, with a maximum of 64 cores.

Memory limit (required): The maximum amount of memory to request, in Gibibytes (Gi).

Storage size (required): The amount of persistent storage to request, in Gibibytes (Gi). The storage volume will be mounted in the /home/matlab.

Attach GPU (optional): If you want to use an Nvidia GPU, enable this option. Select the GPU type and the number of GPUs to request.

Environment variables

Read more about the environment variables in the MATLAB documentation for the Docker container.


The login portal of MATLAB Online opens the application up for anyone to access from a browser, so SSH port forwarding must be used (instead of ingress).

SSH port forward

In Rancher, look up the NodePort at Endpoint using Protocol: TCP

Endpoint                            Protocol           TCP

Log in as user matlab or root, and port forward MATLABs web interface from port 8888

ssh -p 31243 -L 9999:localhost:8888

Open http://localhost:9999 in your web browser.

Web interface

Log in using your MathWorks account, and access the application

matlab web


Default packages

No toolboxes or packages are installed in mathworks/matlab.

This lists the default toolboxes in mathworks/matlab-deep-learning

>> matlab.addons.installedAddons

                Name                         Version    Enabled    Identifier
_________________________________________    _______    _______    __________

"Signal Processing Toolbox"                  "9.1"       true         "SG"   
"Computer Vision Toolbox"                    "10.3"      true         "VP"   
"Deep Learning Toolbox"                      "14.5"      true         "NN"   
"Statistics and Machine Learning Toolbox"    "12.4"      true         "ST"   
"Image Processing Toolbox"                   "11.6"      true         "IP"   
"MATLAB Coder"                               "5.5"       true         "ME"   
"GPU Coder"                                  "2.4"       true         "GC"   
"Parallel Computing Toolbox"                 "7.7"       true         "DM"   
"Text Analytics Toolbox"                     "1.9"       true         "TA"   

Default support packages

>> matlabshared.supportpkg.getInstalled

                           Name                             Version     Base Product     
----------------------------------------------------------- ------- ---------------------
Deep Learning Toolbox Model for AlexNet Network             22.2.0  Deep Learning Toolbox
Deep Learning Toolbox Importer for Caffe Models             22.2.0
Deep Learning Toolbox Model for GoogLeNet Network           22.2.0  Deep Learning Toolbox
GPU Coder Interface for Deep Learning Libraries             22.2.0
Deep Learning Toolbox Model for Inception-ResNet-v2 Network 22.2.0  Deep Learning Toolbox
Deep Learning Toolbox Model for Inception-v3 Network        22.2.0  Deep Learning Toolbox
Deep Learning Toolbox Converter for TensorFlow models       22.2.0
MATLAB Coder Interface for Deep Learning Libraries          22.2.0
Deep Learning Toolbox Converter for ONNX Model Format       22.2.0
Deep Learning Toolbox Model for ResNet-101 Network          22.2.0  Deep Learning Toolbox
Deep Learning Toolbox Model for ResNet-18 Network           22.2.0  Deep Learning Toolbox
Deep Learning Toolbox Model for ResNet-50 Network           22.2.0  Deep Learning Toolbox

Install packages at runtime

Add-on Explorer is not supported on MATLAB Online.

Packages from MATLAB File Exchange can be installed using the MATLAB Command Window

net = mobilenetv2();
Error using mobilenetv2
mobilenetv2 requires the Deep Learning Toolbox Model for MobileNet-v2 Network support 
package for the pretrained weights. 
To install this support package, use the Add-On Explorer. To obtain the untrained
layers, use mobilenetv2('Weights','none'), which does not require the support package.

Open Deep Learning Toolbox Model for MobileNet-v2 Network, right-click Download, and Copy Link.

websave('mobilenetv2.mlpkginstall', '')

Continue with the example

net = mobilenetv2();

Verify GPU Environment

Use the MATLAB Command Window to verify the GPU Code Generation Environment

gpuEnvObj = coder.gpuEnvConfig;
gpuEnvObj.BasicCodegen = 1;
gpuEnvObj.BasicCodeexec = 1;
gpuEnvObj.DeepLibTarget = 'tensorrt';
gpuEnvObj.DeepCodeexec = 1;
gpuEnvObj.DeepCodegen = 1;
results = coder.checkGpuInstall(gpuEnvObj)

The output should be

Compatible GPU           : PASSED 
CUDA Environment         : PASSED 
    Runtime   : PASSED 
    cuFFT     : PASSED 
    cuBLAS    : PASSED 
cuDNN Environment        : PASSED 
TensorRT Environment     : PASSED 
Host Compiler            : PASSED 
Basic Code Generation    : PASSED 
Basic Code Execution     : PASSED 
Deep Learning (TensorRT) Code Generation: PASSED 
Deep Learning (TensorRT) Code Execution: PASSED 

results = 

  struct with fields:

                 gpu: 1
                cuda: 1
               cudnn: 1
            tensorrt: 1
        hostcompiler: 1
        basiccodegen: 1
       basiccodeexec: 1
         deepcodegen: 1
        deepcodeexec: 1
    tensorrtdatatype: 1
           profiling: 0


Examples are available under /opt/matlab/R2022b/examples/

GPU Code Generation: The Mandelbrot Set


Run MATLAB Functions on Multiple GPUs


Read more

Create a custom MATLAB image:

The web browser interface is provided by matlab-proxy

Last update: 2023-08-15
Created: 2022-12-27