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    <p>That's the standard way of using persistent variables in Matlab. You're doing what you're supposed to. There will be noticable overhead for it, but your timings do seem kind of surprisingly high.</p> <p>Here's a similar test I ran in 32-bit Matlab R2009b on a 3.0 GHz Intel Core 2 QX9650 machine under Windows XP x64. Similar results on other machines and versions. About 5x faster than your timings.</p> <p>Test:</p> <pre><code>function call_has_persistent for i = 1:200000 has_persistent(); end function has_persistent persistent CONSTANTS if isempty(CONSTANTS) CONSTANTS = 42; end </code></pre> <p>Results:</p> <pre><code> 0.89 200000 7 persistent CONSTANTS 0.25 200000 8 if isempty(CONSTANTS) </code></pre> <p>What Matlab version, OS, and CPU are you running on? What does CONSTANTS get initialized with? Does Matlab's bench() output seem reasonable for your machine? </p> <p>Your timings do seem high. There may be a bug or config issue there to fix. But if you really want to get Matlab code fast, the standard advice is to "vectorize" it: restructure the code so that it makes fewer function calls on larger input arrays, and makes use of Matlab's built in vectorized functions instead of loops or control structures, to avoid having 200,000 calls to the function in the first place. If possible. Matlab has relatively high overhead per function or method call (see <a href="https://stackoverflow.com/questions/1693429/matlab-oop-is-it-slow-or-am-i-doing-something-wrong/1745686#1745686">Is MATLAB OOP slow or am I doing something wrong?</a> for some numbers), so you can often get more mileage by refactoring to eliminate function calls instead of making the individual function calls faster.</p> <p>It may be worth benchmarking some other basic Matlab operations on your machine, to see if it's just "persistent" that seems slow. Also try profiling just this little call_has_persistent test script in isolation to see if the context of your function makes a difference.</p>
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