Название: MATLAB Parallel Computing Toolbox User’s Guide (R2023b)Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: September 2023
Страниц: 1216
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Perform parallel computations on multicore computers, GPUs, and computer clusters.
Parallel Computing Toolbox lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—enable you to parallelize MATLAB applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
The toolbox lets you use the full processing power of multicore desktops by executing applications on workers (MATLAB computational engines) that run locally. Without changing the code, you can run the same applications on clusters or clouds (using MATLAB Parallel Server). You can also use the toolbox with MATLAB Parallel Server to execute matrix calculations that are too large to fit into the memory of a single machine.
Parallel Computing Toolbox provides you with tools for a local cluster of workers on your client machine. MATLAB Parallel Server software allows you to run as many MATLAB workers on a remote cluster of computers as your licensing allows.
Parallel Computing Toolbox extends the tall arrays and mapreduce capabilities built into MATLAB so that you can run on local workers for improved performance. You can then scale tall arrays and mapreduce up to additional resources with MATLAB Parallel Server on traditional clusters or Apache Spark and Hadoop clusters. You can also prototype distributed arrays on the desktop and then scale up to additional resources with MATLAB Parallel Server.
Most MathWorks products enable you to run applications in parallel. For example, Simulink models can run simultaneously in parallel, as described in “Running Multiple Simulations” (Simulink). MATLAB Compiler and MATLAB Compiler SDK software let you build and deploy parallel applications; for example, see the “Parallel Computing” section of MATLAB Compiler “Standalone
Applications” (MATLAB Compiler).
Several MathWorks products now offer built-in support for the parallel computing products, without requiring extra coding. For the current list of these products and their parallel functionality, see Parallel Computing Support in MATLAB and Simulink Products.
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