Parallel and GPU Computing Tutorials, Part 5: Batch Processing

From the series: Parallel and GPU Computing Tutorials

Harald Brunnhofer, MathWorks

Offload serial and parallel programs using the batch command, and use the Job Monitor.  

Product Focus

  • Parallel Computing Toolbox

Series: Parallel and GPU Computing Tutorials

Part 1: Product Landscape
Get an overview of parallel computing products used in this tutorial series.

Part 2: Prerequisites and Setting Up
Review hardware and product requirements for running the parallel programs demonstrated in Parallel Computing Toolbox™ tutorials.

Part 3: Quick Success with parfor
Review an introductory parfor example using Parallel Computing Toolbox™.

Part 4: Deeper Insights into Using parfor
Convert for-loops to parfor-loops, and learn about factors governing the speedup of parfor-loops using Parallel Computing Toolbox™.

Part 5: Batch Processing
Offload serial and parallel programs using batch command, and use the Job Monitor.

Part 6: Scaling to Clusters and Cloud
Learn about considerations for using a cluster, creating cluster profiles, and running code on a cluster with MATLAB Distributed Computing Server™.

Part 7: spmd - Parallel Code Beyond parfor
Execute code simultaneously on workers, access data on worker workspaces, and exchange data between workers using Parallel Computing Toolbox™ and MATLAB Distributed Computing Server™.

Part 8: Distributed Arrays
Perform matrix math on very large matrices using distributed arrays in Parallel Computing Toolbox™.

Part 9: GPU Computing with MATLAB
Learn about using GPU-enabled MATLAB functions, executing NVIDIA® CUDA™ code from MATLAB®, and performance considerations.