Benchmarks

Examples that measure the performance of parallel code

Topics

Benchmark Cluster Workers
This example shows how to run the MATLAB benchmark on your cluster workers.
Benchmark Your Cluster with the HPC Challenge
This example shows how to evaluate the performance of a compute cluster with the HPC Challenge Benchmark.
Resource Contention in Task Parallel Problems
This example looks at why it is so hard to give a concrete answer to the question "How will my (parallel) application perform on my multi-core machine or on my cluster?" The answer most commonly given is "It depends on your application as well as your hardware," and we will try to explain why this is all one can say without more information.

Featured Examples

Use parfor to Speed Up Monte-Carlo Code

Use parfor-loops to speed up Monte-Carlo code.

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$Benchmarking A\b$

Benchmarking A\b

Benchmark solving a linear system on a cluster. The MATLAB® code to solve for x in A*x = b is very simple. Most frequently, one uses matrix left division, also known as mldivide or the backslash operator (\), to calculate x (that is, x = A\b). Benchmarking the performance of matrix left division on a cluster, however, is not as straightforward.

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$Benchmarking A\b on the GPU$

Benchmarking A\b on the GPU

Looks at how we can benchmark the solving of a linear system on the GPU. The MATLAB® code to solve for x in A*x = b is very simple. Most frequently, we use matrix left division, also known as mldivide or the backslash operator (\), to calculate x (that is, x = A\b).

Open Script