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Mathlab Parallel Computing Toolbox

  • 01861-SW-MATHLAB-001

  • 01861-SW-MATHLAB-001

  • 01861-SW-MATHLAB-001

Parallel Computing Toolbox Perform parallel computations on multicore computers, GPUs, and clusters.

Manufactured by:

MathWorks

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Need Help Ordering?
Call +88 01714243446

Stock
Limited

Custom Pricing

Get A Quote

Overview

Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using MATLAB® and Simulink® on multicore and multiprocessor computers. Parallel processing constructs such as parallel for-loops, distributed arrays, parallel numerical algorithms, and message-passing functions let you implement task- and data-parallel algorithms in MATLAB at a high level without programming for specific hardware and network architectures. As a result, converting serial MATLAB.

Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using MATLAB® and Simulink® on multicore and multiprocessor computers. Parallel processing constructs such as parallel for-loops, distributed arrays, parallel numerical algorithms, and message-passing functions let you implement task- and data-parallel algorithms in MATLAB at a high level without programming for specific hardware and network architectures. As a result, converting serial MATLAB applications to parallel MATLAB applications requires few code modifications and no programming in a low-level language. You can run your applications interactively or offline, in batch environments.

Specification

  • SSupport for data-parallel and task-parallel application development
  • Ability to annotate code segments with parfor (parallel for-loops) and spmd (single program multiple data) for implementing task- and data-parallel algorithms
  • High-level constructs such as distributed arrays, parallel algorithms, and message-passing functions for processing large data sets on multiple processors
  • Ability to run eight workers locally on a multicore desktop
  •  Integration with MATLAB Distributed Computing Server for cluster- and grid-based applications that use any scheduler or any number of workers
  • Interactive and batch execution modes

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