User`s guide

1 Getting Started
1-2
Parallel Computing Toolbox Product Description
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—let you parallelize
MATLAB
®
applications without CUDA or MPI programming. You can use the toolbox
with Simulink
®
to run multiple simulations of a model in parallel.
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 a computer cluster or a grid
computing service (using MATLAB Distributed Computing Server™). You can run
parallel applications interactively or in batch.
Key Features
• Parallel for-loops (parfor) for running task-parallel algorithms on multiple processors
• Support for CUDA-enabled NVIDIA GPUs
• Full use of multicore processors on the desktop via workers that run locally
• Computer cluster and grid support (with MATLAB Distributed Computing Server)
• Interactive and batch execution of parallel applications
• Distributed arrays and spmd (single-program-multiple-data) for large dataset
handling and data-parallel algorithms