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As described on the help page ?updates,Maple17,Performance, Maple 17 uses a new data structure for polynomials with integer coefficients. Our goal was to improve the performance and parallel speedup of polynomial algorithms that underpin much of the system and create a platform for large scale polynomial computations. Shown below is the new representation for 9xy3z

Hello Maple wizards,

I have two questions for you today.

First, a program I'm developing in Maple 15 does frequent matrix multiplication with a constant float[8] matrix. I hope to take advantage of multiple processors in my 6-way desktop processor and/or CUDA features of the Nvidia GPU card. The program is large enough that maintainability and good programming practice dictate that it be broken down into multiple procs. In addition, I'm considering...

How to speedup them? There are more than 20 functions that are evaluated one by one. Is option 'remember' + permanent remembered item of pure symbolic calculation can speedup this process? How also efficiently to do simlify itself? Can i actually use more kernels in one session or to paralilize available one?

The procedure p gives an approximation for Pi. Idea is to place a unit circle in a unit square, throw in some random points (which eventually will be plotted into this figure) and count the points inside the circle. For large n, the quotient n_circle/n_square should tend to Pi/4. But for large n, there may be faster ways to program this, what would you improve ? But keep the principle of this algorithm as it is.  I'd love to have at least 200k points, but this takes annoying 25s on my machine on each run....

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