Tag Archives: Performance

69 relevant articles found:

Parsing XML strings

Matlab’s xmlread function cannot process XML data directly, but this can easily be overcome.

Categories: Low risk of breaking in future versions, Semi-documented feature, Stock Matlab function
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Quirks with parfor vs. for

Parallelizing loops with Matlab’s parfor might generate unexpected results. Users beware!

Categories: Guest bloggers, Medium risk of breaking in future versions, Memory, Stock Matlab function, Undocumented feature
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7 Comments

Afterthoughts on implicit expansion

The new implicit expansion feature of Matlab R2016b can break user code in unexpected ways.

Categories: Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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11 Comments

Speeding up Matlab-JDBC SQL queries

Fetching SQL ResultSet data from JDBC into Matlab can be made significantly faster.

Categories: Java, Low risk of breaking in future versions, Toolbox, Undocumented feature
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5 Comments

Zero-testing performance

Subtle changes in the way that we test for zero/non-zero entries in Matlab can have a significant performance impact.

Categories: Guest bloggers, Low risk of breaking in future versions
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5 Comments

A few parfor tips

The parfor (parallel for) loops can be made faster using a few simple tips.

Categories: Medium risk of breaking in future versions, Public presentation, Undocumented function
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5 Comments

rmfield performance

The performance of the builtin rmfield function (as with many other builtin functions) can be improved by simple profiling.

Categories: Guest bloggers, Low risk of breaking in future versions, Stock Matlab function
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5 Comments

Viewing saved profiling results

We can easily use saved profiling results to analyze, view and compare profiling results of multiple runs.

Categories: Desktop, Low risk of breaking in future versions, Semi-documented function, Stock Matlab function, Undocumented feature
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Convolution performance

Matlab’s internal implementation of convolution can often be sped up significantly using the Convolution Theorem.

Categories: Low risk of breaking in future versions, Stock Matlab function, Undocumented feature
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4 Comments

Callback functions performance

Using anonymous functions in Matlab callbacks can be very painful for performance. Today’s article explains how this can be avoided.

Categories: GUI, Handle graphics, Low risk of breaking in future versions
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11 Comments