Because the only thing I do here is operate on memory, I can estimate the efficiency of this code by calculating the obtained effective memory bandwidth and comparing it to the hardware memory bandwidth of my computer: eff_bandwidth = numel(x) * 8 bytes per double * 2 / time It seems to be very fast (faster at least than memory allocation). Let's call it method 1 (from the value assigned to x). The simplest way is to write: tic x(:) = 1 toc In practice you would do it differently, e.g., x = value*ones(1e8,1), but the point here is to investigate the performance of vector indexing. Having x I would like to set all its entries to the same value. First, I allocate an empty vector x: tic x = zeros(1e8,1) toc
The example codes shown below are as fundamental as it gets: I assign a scalar value to all vector entries. Investigating performance of vector indexing The bottom line: core MATLAB functionality is efficient and trying to outperform it using MATLAB code is hard, if not impossible.
Loops in MATLAB are slow (despite the JIT) and should generally be avoided if the algorithm can be expressed in a native, 'vectorized' manner.MATLAB is very well optimized when it comes to the built-in functions and the fundamental language features, such as indexing vectors and matrices.My question is motivated by simple observations, which somewhat undermine the beliefs/assumptions often held/made by experienced MATLAB users:
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