Comparison with a hand-written loop implementation.

Speed test: matrix inversion

Comparison with an implementation for matrices stored as 2-D arrays.

As of 2017-02-23 2-D arrays had roughly 2 times the speed of the 1-D flatmat implementation (just above).
Not good? On the other hand, for matrix multiplication (and xvmxv) 1-D goes ca 5 to 10 times faster.
So there is a tradeoff, depending on the type of application.

Comparison with an implementation directly in 1-D.

Speed test: vector-matrix product (x-V)^T * M * (x-V)

Measure the speed of the product (x-V)^T * M * (x-V) where x and V are vectors, and M a square matrix. This is useful when computing the exponent term in a Gaussian probability density function.

Comparison with a hand-written implementation (loops).

Code source

The source files used for the tests. Also browsable on GitHub