t = bench measures the execution time of six different benchmarking tasks
on your computer and compares the results to several benchmark computers. The function:
Returns a 1-by-6 vector with the measured execution times
Displays execution times for the benchmark computers
Creates a bar graph that ranks the computers based on their speed
A benchmark is intended to compare the performance of one particular MATLAB® release on different computers. It does not offer direct comparisons between different MATLAB releases because tasks and problem sizes change from release to release.
t = bench( runs each of the six tasks
N times and returns an
N-by-6 array with the
execution times. If
N is zero, the function does not run any of the tasks
on your computer, but instead displays the execution times for other computers and compares
Fluctuations of 5–10% in the measured times of repeated runs on a single computer are normal.
Measure the execution time of the six benchmarking tasks on your computer and compare the results to other benchmark computers.
t = bench
t = 1×6 1.8401 1.0431 0.8902 1.1349 2.3205 5.0333
N— Number of times to run tasks
Number of times to run the six tasks, specified as a nonnegative integer.
The six benchmarking tasks are listed in this table.
|LU||Perform ||Floating-point, regular memory access|
|FFT||Perform ||Floating-point, irregular memory access|
|ODE||Solve van der Pol equation with ||Data structures and MATLAB function files|
|Sparse||Solve a symmetric sparse linear system||Mixed integer and floating-point|
|2-D||Plot Lissajous curves||2-D line drawing graphics|
|3-D||Display colormapped ||3-D animated OpenGL graphics|
The LU and FFT tasks involve large matrices and long vectors.
The 2-D and 3-D tasks measure graphics performance, including support for
hardware-accelerated graphics. The
function provides information about the graphics renderer implementation that MATLAB uses. For example, this command gets the information for the current axes and
stores it in a structure called
info = rendererinfo(gca)
Behavior changed in R2020a
Starting in R2020a, problem sizes have increased for the numerical computation tasks
(LU, FFT, ODE, and Sparse) so that the ranking of computers using
test results are not dominated by the 2-D and 3-D graphics tasks. In previous releases, the
2-D and 3-D tasks take significantly longer to complete compared to the numerical
computation tasks and therefore contribute disproportionately to the ranking of
This table shows different task execution times in R2020a using a Windows® 10, Intel® Xeon® W-2133 @ 3.60 GHz test system. The measured values are expressed in seconds.
|Task||New Problem Sizes||Old Problem Sizes|