Performance of Java matrix math libraries? [closed]

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I’m the author of Java Matrix Benchmark (JMatBench) and I’ll give my thoughts on this discussion.

There are significant difference between Java libraries and while there is no clear winner across the whole range of operations, there are a few clear leaders as can be seen in the latest performance results (October 2013).

If you are working with “large” matrices and can use native libraries, then the clear winner (about 3.5x faster) is MTJ with system optimised netlib. If you need a pure Java solution then MTJ, OjAlgo, EJML and Parallel Colt are good choices. For small matrices EJML is the clear winner.

The libraries I did not mention showed significant performance issues or were missing key features.

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