Parallel Computing Toolbox
Product Description
- Parallel Computing Toolbox Key Features
- Programming Parallel Applications
- Using Built-In Parallel Algorithms in Other MathWorks Products
- Speeding Up Task-Parallel Applications
- Speeding Up MATLAB Computations with GPUs
- Scaling Up to Clusters, Grids, and Clouds Using MATLAB Distributed Computing Server
- Implementing Data-Parallel Applications using the Toolbox and MATLAB Distributed Computing Server
- Running Parallel Applications Interactively and as Batch Jobs
Speeding Up MATLAB Computations with GPUs
Parallel Computing Toolbox provides GPUArray, a special array type with several associated functions that lets you perform computations on CUDA-enabled NVIDIA GPUs directly from MATLAB. Functions include fft, element-wise operations, and several linear algebra operations such as lu and mldivide, also known as the backslash operator (\). The toolbox also provides a mechanism that lets you use your existing CUDA-based GPU kernels directly from MATLAB.
Learn more about GPU computing with MATLAB.
GPU computing with MATLAB. Using GPUArrays and GPU-enabled MATLAB functions help speed up MATLAB operations without low-level CUDA programming.
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Free Parallel Computing Interactive Kit
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