> The usual solution is to devectorized your code and to use loops (except for matrix multiplication if you have large matrices).
I am hopeful that ParallelAccelerator.jl [1][2] or similar projects can enable fast vectorized Julia code [1] https://github.com/IntelLabs/ParallelAccelerator.jl [2] http://julialang.org/blog/2016/03/parallelaccelerator On Sun, May 8, 2016 at 3:37 PM, feza <[email protected]> wrote: > I mean the revised script runs just as fast if not a tad faster with the > latest master as it does on 0.4.5 : ) > > > On Sunday, May 8, 2016 at 5:20:08 PM UTC-4, Patrick Kofod Mogensen wrote: >> >> Same as v0.4, or same as before you changed the code? >> >> On Sunday, May 8, 2016 at 8:55:00 PM UTC+2, feza wrote: >>> >>> roughly the same speed. >>> >>> On Sunday, May 8, 2016 at 2:44:19 PM UTC-4, Patrick Kofod Mogensen wrote: >>>> >>>> out of curiosity, what about v0.5? >>> >>> -- [email protected]
