- fixed point code can take longer than floating point (but fixed point can be used on devices that have no floating point unit)
- code that does calculations on sufficiently large arrays often ends up calling multithreaded high-performance libraries that use all of the cores. Generated C/C++ code does not call those libraries and so operates single-core. You can use https://www.mathworks.com/help/matlab/ref/maxnumcompthreads.html to test to see if this is the reason the generated code is slower (that is, by restricting your MATLAB to one thread.)
some questions about matlab coder
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Hi
I am doing my senior project on 5G simulations in matlab. We are doing the QAM using precoder and some modulation functions. We want to convert the code we have into C or C++. We used the matlabe code gen and we converted to C. We were surprised by how slow the C code is compared to matlab. It takes 260 sec for C to run one trial while only 90 sec on matlab. One of the thing we did is set the code gen to use dynamic allocation instead of static. I am looking for some recommendation or suggestions on how to produce a fast enough C code. Is that possible or we have to write the code fro scratch. Thanks
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Ryan Livingston
am 27 Apr. 2018
Bearbeitet: Ryan Livingston
am 27 Apr. 2018
MATLAB Coder added the ability for the generated code to call LAPACK in R2016a:
and FFTW in R2017b:
Using these will give you optimized linear algebra and FFT routines respectively.
Antworten (3)
Ji Lee
am 25 Apr. 2018
Reducing the usage of dynamic memory allocation is one of the general optimization strategies one can start with when trying to improve the performance of generated code. We do have a useful documentation section that describes various optimizations and patterns. I've linked it below. Included in the first several topics linked from this section is a discussion on variable sizing and dynamic memory allocations.
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