ARG MATLAB 2012 CODE
ARG MATLAB 2012 SERIES
ARG MATLAB 2012 DOWNLOAD

The answer is that our simple attempt to edit in-place conflicts with MatlabвЂ™s internal copy-on-write mechanism. What is going on? MatlabвЂ™s copy-on-write mechanism

In fact, under some conditions this kind of uncontrolled editing in-place can crash the entire Matlab environment with a segfault. Uhoh, spooky we expected that running fast_median_tweaked would change input A, but somehow it has also changed B, even though B is supposed to be an independent copy. Given that in-place editing is not officially supported in Matlab Mex extensions, what do we have to do to make it work? Let us look at the normal, input-copying fast_median function as a starting point: But as we have shown, it can be an important capability to have if speed and memory use are critical to an application.

ARG MATLAB 2012 CODE

This is not necessarily a bad thing many people feel that modifying input data is bad programming practice and makes code harder to maintain. Modifying a functionвЂ™s input is common in many languages, but in Matlab there are only a few special conditions under which this is officially sanctioned. This is how the in-place method is able to run without using new memory it operates on the existing array rather than making a copy. The fast_median function is the next CPU spike it has a similar step up and down in memory use, but it is much faster.ДЇinally, in the case of fast_median_ip we see something different there is a spike in CPU use, but memory use stays flat the in-place version is faster and more memory efficient because it does not make a copy of the input data.ДЄs you can see, all three methods get the same answer, but median and fast_median do not modify A in the workspace, whereas after running fast_median_ip, input array A has changed. You can see that over that period memory use stepped up again, and then stepped back down the median function makes a copy of the entire input data, and then throws its copy away when it is finished this is expensive in terms of time and resources. The second CPU spike is the largest that is MatlabвЂ™s median function. The first spike in CPU is when we created the test data vector memory use also steps up at that time. You can see four spikes in CPU use, and some associated changes in memory allocation: What is the difference? Let us look behind the scenes here are the CPU and memory traces from my system monitor after running the above: The second point is that the in-place version, fast_median_ip, yields an additional speed improvement. Besides being a shameless plug, this demonstrates why we might want to write a Mex function in the first place: rewriting the median function in pure Matlab would be slow, but using C++ we can significantly improve on the status quo. This is because fast_median uses a more efficient algorithm see the nth_element page for more details. This example illustrates a few general points: first, fast_median is significantly faster than MatlabвЂ™s native median function. In terms of the execution time for the different functions, your mileage may vary depending on factors such as: your system, what Matlab version you are running, and whether your test data is arranged in a single vector or a multicolumn array. If you try running this, be careful not to make A too large tune the example according to the memory available on your system. Let us try a few function calls to see how editing in-place can save time and memory: The examples are fairly self-explanatory, so if you do not want to try the code you should be okay just following along.

ARG MATLAB 2012 DOWNLOAD

You can download the package and play with the code if you want. To demonstrate the techniques in this article, I use the fast_median function, which is part of my nth_element package on MatlabвЂ™s File Exchange. In this article, I will introduce the problem and show a simple solution that exhibit the basic implementation details of MatlabвЂ™s internal copy-on-write mechanism. Unfortunately, editing arrays in-place from Mex extensions is not officially supported in Matlab, and doing it incorrectly can cause data inconsistencies or can even cause Matlab to crash. The Matlab language itself has some limited support for in-place editing, but when we are really concerned with speed we often turn to writing C/C++ extensions using the Mex interface.

ARG MATLAB 2012 SERIES

I would like to welcome Matlab Mex power-user Peter Li to a first in a short series of articles about undocumented aspects of Mex programingД®diting Matlab arrays in-place can be an important technique for optimizing calculations, especially when handling data that use large blocks of memory.

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