The dense multicore examples will take months to run in Flint, since we 
haven't written the code yet! :-)

But your explanation about the cost of conversion in the sparse case 
certainly more than accounts for overall difference in performance.

Giac also has a symbolic front end, too, which Flint and Nemo do not. That 
is certainly important for people to realise.

On Tuesday, 26 September 2017 13:13:06 UTC+2, parisse wrote:
>
>
>
> Le mardi 26 septembre 2017 10:43:10 UTC+2, Bill Hart a écrit :
>>
>> We used to do this, and Daniel noticed that it wasn't really threadsafe.
>>
>
> It would be in my implementation, but inserting requires sometimes memory 
> allocation and it seems to slow down too much. Anyway, as explained 
> earlier, conversions from packed exponent-int128 coefficients to 
> polynomials with unpacked exponents and generic coefficients takes too much 
> time in the sparse case, I think is not worth rewriting a thread-efficient 
> sparse multivariate polynomial multiplication algorithms in giac. For 
> example in the n=12 case, the effective multiplication takes 1.3s on my Mac 
> and conversion takes twice more, in the n=16 case, effective multiplication 
> takes 11.5s and conversion 19s (run export GIAC_DEBUG=6 in a shell or 
> debug_infolevel:=6; in a script to see some details while running giac). 
> It's probably the same problem for Maple with their "native" vs sdmp 
> polynomial representation. This is something that the reader of your 
> benchmarks should keep in mind.
> Thinks are completely different for dense polynomials, because the 
> conversion is dominated by the multiplication time (but fortunately 
> thread-efficient multiplication code is available for giac for these kind 
> of polynomials).
>

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