parallel and gpu computing tutorials -凯发k8网页登录
parallel computing toolbox™ helps you take advantage of multicore computers and gpus. the videos and code examples included below are intended to familiarize you with the basics of the toolbox. they can help show how to scale up to large computing resources such as clusters and the cloud. (scaling up requires access to matlab parallel server™.)
get an overview of parallel computing products used in this tutorial series.
review hardware and product requirements for running the parallel programs demonstrated in parallel computing toolbox tutorials.
review an introductory parfor example using parallel computing toolbox.
convert for-loops to parfor-loops, and learn about factors governing the speedup of parfor-loops using parallel computing toolbox.
offload serial and parallel programs using batch command, and use the job monitor.
learn about considerations for using a cluster, creating cluster profiles, and running code on a cluster with matlab parallel server.
execute code simultaneously on workers, access data on worker workspaces, and exchange data between workers using parallel computing toolbox and matlab parallel server.
perform matrix math on very large matrices using distributed arrays in parallel computing toolbox.
learn about using gpu-enabled matlab functions, executing nvidia cuda code from matlab, and performance considerations.