Cloud Clusters created with MATLAB R2019b are currently running MATLAB Release R2019b Update 2
MATLAB Release 2019b Updates Release Notes
When you select the MATLAB release for your cluster (see table below for currently supported releases), it will always run with the latest available version of MATLAB for that release. Updates are cumulative.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB® version R2017b has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2019b, R2019a, R2018b, or R2018a | As newer versions of MATLAB become supported, the support for older versions will be removed in future releases. |
Cluster Shared State
The cluster attribute Shared State enables Cloud Center to authorize users to submit jobs to or interact with a cluster from MATLAB. The Shared State may be Personal Cluster (accessible only by you) or Shareable Cluster (accessible to people you have explicitly given access to via a white list). The default Shared State attribute of a cluster is Personal Cluster. This authorization control is unrelated to accessing the cluster via SSH.
For Shareable Clusters, the person creating the cluster must expressly add authorized users to the Shared With field.
Cloud Center clusters created for MATLAB releases prior to R2019b did not have clusters with the Shared State attribute. Those clusters are all implicitly shareable clusters, as any user who imports a cluster profile is authorized to submit jobs to or interact with the cluster from MATLAB. The inbound firewall rules for these clusters are managed only by Global Cluster Access rules.
For more information, see Sharing Options for Clusters.
Auto-Manage Cluster Access
The cluster attribute Auto-Manage Cluster Access allows Cloud Center to manage a cluster’s inbound firewall rules on a cluster-by-cluster basis. Auto-Manage Cluster Access is enabled by default for Personal Clusters.
Clusters created prior to R2019b are Shareable Clusters, whose inbound firewall rules are managed only by Global Cluster Access rules.
For more information, see Manage Cluster Access Automatically.
Cloud Center is currently running MATLAB Release R2019b Update 1
Cloud Center now supports MATLAB Release R2019a Update 6
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2017b has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2019b, R2019a, R2018b, or R2018a | As newer versions of MATLAB become supported, the support for older versions will be removed in future releases. |
Cloud Center is currently running MATLAB Release R2019a Update 5
Cloud Center now supports MATLAB Release R2018b Update 5
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2017a has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2019a, R2018b, R2018a, or R2017b | As newer versions of MATLAB become supported, the support for older versions will be removed in future releases. |
Cloud Center is currently running MATLAB Release R2019a Update 4
Release notes for MATLAB Release R2019a Update 4 are available on the MathWorks Downloads page under Related Links > R2019a Updates Release Notes.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2017a has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2019a, R2018b, R2018a, or R2017b | As newer versions of MATLAB become supported, the support for older versions will be removed in future releases. |
Support for MATLAB Release R2019a Update 3 including three additional pretrained convolutional neural networks (CNN) for deep learning
You can run MATLAB R2019a Update 3 on Cloud Center instances,
including support for three additional pre-trained convolutional
neural network (CNN) models: NASNet-Large, NASNet Mobile, and
ShuffleNet. You can use these pretrained models for
classification and transfer learning. You can access the models
using the functions nasnetlarge
, nasnetmobile
, and shufflenet
. For details, see Deep Learning in Parallel and in the Cloud (Deep Learning Toolbox) and Pretrained Deep Neural Networks (Deep Learning Toolbox).
MathWorks® sign-on includes Cloud Center sign-on
Signing in to MathWorks simultaneously signs you in to Cloud Center using your MathWorks account.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2017a has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2019a, R2018b, R2018a, or R2017b | As newer versions of MATLAB become supported, the support for older versions will be removed in future releases. |
Support for MATLAB Release R2019a including pretrained convolutional neural networks (CNN) for deep learning
You can run MATLAB Release R2019a on Cloud Center instances,
including support for pretrained convolutional neural network
(CNN) models. These networks are now available on all instances
for MATLAB Release R2019a: AlexNet, DenseNet-201, GoogLeNet
(trained using ImageNet and Places365 data sets),
Inception-ResNet-v2, Inception-v3, MobileNet-v2, ResNet-18,
ResNet-50, Resnet-101, SqueezeNet, VGG-16, VGG-19, and Xception.
You can access the models using the functions alexnet
, densenet201
, googlenet
, inceptionresnetv2
, inceptionv3
, mobilenetv2
, resnet18
, resnet50
, resnet101
, squeezenet
, vgg16
, vgg19
, and
xception
. You can use these pretrained models
for classification and transfer learning. For details, see Deep Learning in Parallel and in the Cloud (Deep Learning Toolbox), and Pretrained Deep Neural Networks (Deep Learning Toolbox).
Automatic Cluster Resizing: Resize Cloud Center clusters on Amazon based on usage
You can create cloud clusters using MATLAB Release R2019a that resize automatically based on usage. These clusters grow or shrink to allocate the optimal number of workers for your submitted tasks. For more information, see Resize Clusters Automatically.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2017a will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | MATLAB versions R2019a, R2018b, R2018a, or R2017b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2016b has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2018b, R2018a, R2017b, or R2017a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for the Amazon EC2® Classic network type has been removed. | Errors | Set up a new cluster using the Amazon EC2 Virtual Private Cloud (VPC) network type. | Amazon® Web Services withdrew support for the EC2 Classic network for new accounts in 2013. To continue using MATLAB with cloud resources, see Configure AWS VPC for Cloud Center. |
Cloud Center support for running MATLAB version R2016b will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | MATLAB versions R2018b, R2018a, R2017b, or R2017a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for the Amazon EC2 Classic network type will be removed in a future release. | Warns | Set up a new cluster using the Amazon EC2 Virtual Private Cloud (VPC) network type. | Amazon Web Services withdrew support for the EC2 Classic network for new accounts in 2013. To continue using MATLAB with cloud resources, see Configure AWS VPC for Cloud Center. |
Cloud Center support for running MATLAB version R2016b will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | MATLAB versions R2018b, R2018a, R2017b, or R2017a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Support for MATLAB Release R2018b including pretrained convolutional neural networks (CNN) for deep learning
You can run MATLAB Release R2018b on Cloud Center instances,
including support for pretrained convolutional neural network
(CNN) models. These networks are now available on all instances
for MATLAB Release R2018b: AlexNet, DenseNet-201, GoogLeNet,
Inception-ResNet-v2, Inception-v3, ResNet-18, ResNet-50,
Resnet-101, SqueezeNet, VGG-16, and VGG-19. You can access the
models using the functions alexnet
, densenet201
, googlenet
, inceptionresnetv2
, inceptionv3
, resnet18
, resnet50
, resnet101
, squeezenet
, vgg16
, and
vgg19
. You can use
these pretrained models for classification and transfer
learning. For details, see Deep Learning in Parallel and in the Cloud (Deep Learning Toolbox), and Pretrained Deep Neural Networks (Deep Learning Toolbox).
MATLAB worker Amazon Machine Images (AMI) now support CUDA 9.0
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2016b will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | MATLAB versions R2018b, R2018a, R2017b, or R2017a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2016a has been removed. For more information on the migration policy, see Requirements for Using Cloud Center. | Errors | MATLAB versions R2018a, R2017b, R2017a, or R2016b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Create clusters in dedicated headnode mode
Starting this release, you can create clusters in dedicated headnode mode. When enabled, the headnode instance exclusively runs management services, such as the job manager, and does not host any MATLAB workers. This cluster architecture improves performance. For details, see Use a Dedicated Headnode Instance for Management Services.
Increased maximum number of workers to 1024
You can now create up to 1024
worker machines
in VPC networks for MATLAB R2018a onwards.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2016a will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | MATLAB versions R2018a, R2017b, R2017a, or R2016b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Support for MATLAB Release R2018a including pretrained convolutional neural networks (CNN) for deep learning
You can run MATLAB Release R2018a on Cloud Center instances,
including support for pretrained convolutional neural network
(CNN) models. These networks are now available on all instances
for MATLAB Release R2018a: AlexNet, VGG-16, VGG-19,
GoogLeNet, ResNet-50, and ResNet-101. You can access the models
using the functions alexnet
, vgg16
, vgg19
, googlenet
, resnet50
, and resnet101
. You can use these pretrained models
for classification and transfer learning. For details, see Deep Learning in Parallel and in the Cloud (Deep Learning Toolbox), and Pretrained Deep Neural Networks (Deep Learning Toolbox).
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2016a will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | MATLAB versions R2018a, R2017b, R2017a, or R2016b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2016a will be removed in a future release. For more information on the migration policy, see Requirements for Using Cloud Center. | Warns | Migrate to MATLAB versions R2017b, R2017a, or R2016b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
New pretrained convolutional neural networks (CNN) for deep learning
You can run MATLAB Release R2017b on Cloud Center instances, including support for pretrained convolutional neural network (CNN) models. These networks are now available on all instances for MATLAB R2017b: GoogLeNet, ResNet-50, AlexNet, VGG-16, and VGG-19. You can use these pretrained models for classification and transfer learning. For details, see the white paper Deep Learning with MATLAB and Multiple GPUs, and Pretrained Deep Neural Networks (Deep Learning Toolbox).
Support for new P3 instance types
Cloud Center supports the new P3 instance family. P3s have up to 8 NVIDIA Tesla V100 GPUs and are well suited for high performance general computation including deep learning, modeling and data analysis.
For more details on newly added compute instances and regional availability, see Choose Supported EC2 Instance Machine Types.
Updated IAM Role creation workflow
Cloud Center on-screen instructions are updated to help you through the latest workflow in the Amazon console to create IAM Roles.
For more details, see Create New IAM Role.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2015b has been removed. | Errors | MATLAB versions R2017b, R2017a, R2016b, or R2016a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Support for MATLAB Release R2017b including pretrained convolutional neural networks (CNN) for deep learning
You can run MATLAB Release R2017b on Cloud Center instances,
including support for pretrained convolutional neural network
(CNN) models. These networks are now available on all instances
for MATLAB Release R2017a and MATLAB Release R2017b: AlexNet,
VGG-16, and VGG-19. You can access the models using the
functions alexnet
, vgg16
, and
vgg19
. You can use
these pretrained models for classification and transfer
learning. For details, see the white paper Deep Learning with MATLAB and Multiple GPUs, and
Pretrained Deep Neural Networks (Deep Learning Toolbox).
Support for new G3 instance types
Cloud Center supports the new G3 instance family. G3s have multiple GPUs with high single-precision performance well suited for deep learning, image processing and computer vision.
For more details on newly added compute instances and regional availability, see Choose Supported EC2 Instance Machine Types.
Streamlined workflow for using data in the cloud
To work with data in the cloud, you can upload to Amazon S3, then use datastores to access the data in S3 from the workers in your cluster. For details, see Transfer Data To Amazon S3 Buckets.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2015a has been removed. | Errors | MATLAB versions R2017b, R2017a, R2016b, or R2016a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Cloud Center support for running MATLAB versions R2015b will be removed in a future release. | Warns |
Deep Learning: Pretrained convolutional neural network (CNN) models AlexNet, VGG-16, and VGG-19 are now available on all instances
Three pretrained convolutional neural network (CNN) models are
now available on all instances for MATLAB Release R2017a only:
AlexNet, VGG-16, and VGG-19. You can access the models using the
functions alexnet
, vgg16
, and
vgg19
. These models
are SeriesNetwork
objects. You can use these pretrained
models for classification and transfer learning.
For more details, see Pretrained Deep Neural Networks (Deep Learning Toolbox).
New “Getting Started with Cloud Center” documentation
For details, see Getting Started with Cloud Center.
Support for new Compute Optimized instance types
c4.xlarge, with 2 physical cores and 7.5 GB Memory
c4.2xlarge, with 4 physical cores and 15 GB Memory
c4.4xlarge, with 8 physical cores and 30 GB Memory
c4.8xlarge, with 16 physical cores and 60 GB Memory
c4.8xlarge is the suggested default instance for clusters in a VPC.
For more details on newly added compute optimized instances and regional availability, see Choose Supported EC2 Instance Machine Types.
Support for new Memory Optimized instance types
r4.xlarge, with 2 physical cores and 30.5 GB Memory
r4.2xlarge, with 4 physical cores and 61 GB Memory
r4.4xlarge, with 8 physical cores and 122 GB Memory
r4.8xlarge, with 16 physical cores and 244 GB Memory
r4.16xlarge, with 32 physical cores and 488 GB Memory
For more details on newly added compute optimized instances and regional availability, see Choose Supported EC2 Instance Machine Types.
Support for new Storage Optimized instance types
i3.xlarge, with 2 physical cores, 30.5 GB Memory, and 950 GB ephemeral storage
i3.2xlarge, with 4 physical cores, 61 GB Memory, and 1900 GB ephemeral storage
i3.4xlarge, with 8 physical cores, 122 GB Memory, and 3800 GB ephemeral storage
i3.8xlarge, with 16 physical cores, 244 GB Memory, and 7600 GB ephemeral storage
i3.16xlarge, with 32 physical cores, 488 GB Memory, and 15200 GB ephemeral storage
For more details on newly added compute optimized instances and regional availability, see Choose Supported EC2 Instance Machine Types.
MATLAB Worker Amazon Machine Images (AMI) now support Ubuntu 16.04 LTS
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2015aSP1 has been removed. | Errors | MATLAB versions R2015b, R2016a, R2016b or R2017a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Deep Learning in the cloud
You can use MATLAB with Cloud Center to perform deep learning in the cloud using Amazon Elastic Compute Cloud (Amazon EC2) with new P2 instances. These instances provide access to NVIDIA® Tesla K80 Accelerators with NVIDIA GK210 GPUs that include Error Correcting Code (ECC) memory protection and double precision floating point operations. For details, see the Deep Learning in the Cloud with MATLAB White Paper.
MATLAB worker Amazon Machine Images (AMI) now support CUDA 8.0
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB versions R2015a and R2015aSP1 will be removed in a future release. | Warns | MATLAB versions R2015b, R2016a, R2016b or R2017a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Add local storage on each cluster node
You can now use an Amazon EBS volume of type “General Purpose Solid-State Drive” ( "gp2") as local storage. You can specify existing snapshots to instantiate the volumes. For more information, see Create a Cloud Cluster.
Support for new GPU compute instance types
p2.xlarge, with 2 physical cores and 1 GPU
p2.8xlarge, with 16 physical cores and 8 GPUs
p2.16xlarge, with 32 physical cores and 16 GPUs
For more details on newly added GPU compute instances and regional availability, see Choose Supported EC2 Instance Machine Types.
Support for new Memory Optimized instance types
r3.xlarge, with 2 physical cores and 30.5 GiB Memory
r3.2xlarge, with 4 physical cores and 61 GiB Memory
r3.4xlarge, with 8 physical cores and 122 GiB Memory
r3.8xlarge,with 16 physical cores and 244 GiB Memory
For more details on newly added memory optimized instances and regional availability, see Choose Supported EC2 Instance Machine Types.
MATLAB worker Amazon Machine Images (AMI) have been patched to mitigate CVE-2016-5195
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2014b has been removed. | Errors | MATLAB versions R2015a, R2015b, R2016a, or R2016b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
Use Cloud Center with Amazon Virtual Private Cloud (VPC)
VPC enables Cloud Center users to launch clusters in a virtual network that you define. For more information, see Create a Cloud Cluster.
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2014b will be removed. | Warns | MATLAB versions R2015a, R2015b, R2016a, or R2016b. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |
MATLAB worker Amazon Machine Images (AMI) now support CUDA 7.5
Functionality being removed or changed
Functionality | Result | Use Instead | Compatibility Considerations |
---|---|---|---|
Cloud Center support for running MATLAB version R2014a has been removed. | Errors | MATLAB versions R2014b, R2015a, R2015b, or R2016a. | As newer versions of MATLAB are supported, the support for older versions will be removed in future releases. |