> I'm curious to know if performance of Maple 15 are following the same as 
for Maple 14.

Very similar.  SDMP was refactored for Maple 15.  It's size was cut in half, 
it was made re-entrant to allow parallel polynomial algorithms, and we now 
support Zp for multiprecision p.  We added Kronecker substitution for 
univariate multiplication (calling GMP, sadly version 4.2), and implemented 
powering algorithms in C.  There's some internal stuff for recycling memory 
which makes the parallel multiplication use the same amount of memory as 
sequential.  We needed that for parallel division, which sadly did not ship 
because the Windows scheduler threw monkey wrenches at us.  We fixed the 
issue but it was too late for Maple 15.  There are lots of other goodies in 
the pipeline now.  We have been coding for about 8 months, and Maple 15 is 
just the first 2 months of that.

As for Trip, those results are very impressive.  We have improved the 
performance and scalability of sdmp, but we can't match those results. 
 We're getting a big machine soon so there is a chance to try.  The heap 
algorithms were mainly chosen for their memory use.  For multiplication f*g 
the heap is O(min(#f,#g) + result) and for division f/g = q it is O(#g + 
#q), this is both sequential and in parallel.  We emphasized superlinear 
speedup on a modest number of cores (16 or less) to offer stiff competition 
on the desktop and because higher level algorithms should be parallelized 
too.  We have quite a lot on our plate so we concede the speed crown to Trip 
for now.  I can't say I mind, because the scalability they achieved at 64 
cores is an extremely difficult thing to do.  We're still looking good next 
to Magma and Singular (which Sage uses).  But we're not stingy.  If anyone 
is implementing these algorithms or other sparse algorithms, we're happy to 
discuss details in newsgroups or by email.

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