Parallel Computing Toolbox

Parallel Computing Toolbox

Perform parallel computations on multicore computers, GPUs, and clusters

Scale Up MATLAB Applications

Parallel Computing Toolbox allows your applications to take advantage of computers equipped with multicore processors and GPUs.

Speed Up MATLAB with Multicore Computers

Use parallel for loops (parfor) to run independent iterations in parallel on multicore CPUs, for problems such as parameter sweeps, optimizations, and Monte Carlo simulations. parfor automates the creation of parallel pools and manages file dependencies, so that you can focus on your work. Key functions in several MATLAB and Simulink products have parallel enabled functions. With Parallel Computing Toolbox, these functions can distribute computations across available parallel computing resources. You can execute parallel applications interactively and in batch.

Use Parallel Computing Toolbox to speed up MATLAB and Simulink with additional CPU and GPU resources.

Use Parallel Computing Toolbox to speed up MATLAB and Simulink with additional CPU and GPU resources.

Accelerate MATLAB with GPUs

Parallel Computing Toolbox enables you to use NVIDIA®GPUs directly from MATLAB usinggpuArray. More than 500 MATLAB functions run automatically on NVIDIA GPUs, includingFFT, element-wise operations, and several linear algebra operations such aslumldivide,也被称为反斜杠符(\)。关键的傅nctions in several MATLAB and Simulink products, such as Deep Learning Toolbox, have GPU enabled functions. You can use GPUs without having to write any additional code, so you can focus on your applications rather than performance tuning. Advanced developers can call their own CUDA code directly from MATLAB. You can utilize multiple GPUs on desktop, compute clusters, and cloud environments.

Use GPUArray and GPU-enabled MATLAB functions to help speed up MATLAB operations without low-level CUDA programming.

UsegpuArray和GPU-enabled MATLAB functions to help speed up MATLAB operations without low-level CUDA programming.

Process Big Data

Parallel Computing Toolbox extends thetallarrays andMapReducecapabilities built into MATLAB so that you can run on local workers for improved performance. You can then scaletallarrays andMapReduceup to additional resources with MATLAB Parallel Server on traditional clusters or Apache Spark™ and Hadoop®集群。您还可以在台式机上进行原型分布式数组,然后使用MATLAB并行服务器扩展到其他资源。

Analyze big data sets in parallel using MATLAB tall arrays.

Analyze big data sets in parallel using MATLABtallarrays.

Speed Up Simulink Simulations

With Parallel Computing Toolbox, you can easily run many Simulink simulations at the same time on multiple CPU cores. Easily run the same model with different inputs or parameter settings in Monte Carlo analyses, parameter sweeps, model testing, experiment design, and model optimization.

Run Multiple Simulations in Parallel

Use theparsimfunction to run your simulations in parallel. The function distributes multiple simulations to multicore CPUs to speed up overall simulation time.parsimalso automates the creation of parallel pools, identifies file dependencies, and manages build artifacts, so that you can focus on your design work. You can execute parallel simulations interactively or in batch.

Use the parsim function to run multiple simulations in parallel.

Use the multiple simulations panel orparsimfunction to run your simulations in parallel.

模拟管理器

Simulation manager is integrated withparsim和can be used to monitor and visualize multiple simulations in one window. You can select an individual simulation and view its specifications, as well as use the Simulation Data Inspector to examine simulation results. You can also conveniently run diagnostic tasks or abort simulations.

Monitor multiple simulations in one window.

Monitor multiple simulations in one window with Simulation Manager.

Leverage Parallel-Enabled Simulink Functionality

In addition to usingparsimbatchsimfunctions to run Simulink simulations, there are a number of Simulink products, including Simulink Design Optimization™, Reinforcement Learning Toolbox™, Simulink Test™, and Simulink Coverage™ that provide parallel capability, so you can run simulations in parallel without writing any code.

通过设置标志或万博1manbetx偏好来启用Simulink应用程序进行并行计算。

Parallel simulations can be enabled by a preference or flag setting.

Parallel Computing in Clusters and Clouds

Prototype and debug applications on the desktop or virtual desktop and scale to clusters or clouds without recoding. Develop interactively and move to production with batch workflows.

Run a MATLAB Desktop in Public and Private Clouds

Speed up analysis and simulations by taking advantage of multiple on-demand, high-performance CPU and GPU machines. Run MATLAB and Simulink directly on virtual machines in the Amazon Web Services®(AWS) environment or in Microsoft Azure®.

您还可以通过在NVIDIA GPU Cloud或NVIDIA DGX上的MATLAB深度学习容器中训练神经网络来加快深度学习应用程序。

Run MATLAB and Simulink directly on EC2 instances in the Amazon Web Services (AWS) environment.

Run MATLAB and Simulink directly on EC2 instances in the Amazon Web Services (AWS) environment.

Scale to Clusters with MATLAB Parallel Server

Develop a prototype on your desktop, and scale to a compute cluster or clouds without recoding. Access different execution environments from your desktop just by changing your cluster profile.

Easily scale up your applications using additional cluster and cloud resources without changing your code

Easily scale up your applications using additional cluster and cloud resources without changing your code.