Re: [Gretl-devel] [Gretl-users] When Julia is faster than C and Gretl

On Wed, 21 Feb 2018, Sven Schreiber wrote: One more follow-up on this. We should probably aim to extend the binary matrix transfer facility for R too, and maybe octave. But I'm not going to hold the next release for that; and I should point out that it can be a little fiddly, for two reasons. 1) The gretl_matrix struct employs column-major order, and when we write or read matrices in binary mode we just dump out, or read in, all the values in that order. So when implementing a "foreign" transfer it's important to check the code via round-tripping. In the case of Julia, for example, when reading a binary matrix written by gretl we can't just read (rows * cols) doubles in directly, we have to place the values properly, as in for j=1:c for i=1:r M[i,j] = read(f, Float64) end end as opposed to "read(f, Float64, r*c)", which would scramble the matrix! 2) In gretl_binary_matrix files we standardized on little-endian format. Pretty much everything is little-endian these days, but all the same we should guard against getting total garbage in the case of mixing byte-orders. In the unlikely event that Python or Julia are running on a big-endian machine we need to convert to little-endian format on writing, and from little-endian format on reading. Both of these points are handled in the facilities for Python and Julia in current git. Allin