Items tagged with parallel


As I understand it, Maple will detect and use the available cores in a system, if the calculation is suitable for multi-core use.

As I am installing Maple on a multi-user cluster, using a scheduler to run maple scripts, I want to ensure the maple jobs only use the number of cores allocated to the job.  

Is it possible to set the number of cores used ? 

If I have misunderstood how Maple works (I am new to it), or if there is a section in the documentation which explains this, please point me in the right direction.  I haven't found this info so far.

     Parallel curves on surfaces. The distance between the points of the curves is measured along the curves of intersection of the surface and perpendicular planes.
     (According to tradition, it also does not make sense.)




I attempted to show that two lines are parallel.  I started with a problem in Geometry for which I do not have the solution.

I tried several ways with Maple to show this to be true.  Most of the time, I ended when maple could not determine if a-b = c-d, etc.

brg_proof.txt contains a statement of the problem and my latest maple code.

Question: How should I approach the proof, by the compass and straight edge method?  Is this possible in maple?

Hi all,

I start working with the Grid package.
To familiarize myself with it I ran the "primeChecker" example, which of course has worked perfectly well.

Next I did this (a priori harmless) simple modifications :

  1. within the primeChecker procedure :
    replace  myVal := userData[thisNode+1] :
    by         myVal := userData[thisNode+1, 1] :
  2. before launching the procedure with Grid[Launch] :
    replace  userData := [ .... ] :  #which is a list
    by         userData := [ .... ] :  # the same thing
                 userData := convert(userData, matrix): 

I get the following error message :
error, (in unknown) Matrix index out of range

What does it mean and how can I fix this ?

Thanks in advance

I am (again) trying to get Maple to do some parallel work; using the Threads package.

My actual problem involves a vector function with 6 elements, acting on 6-vectors. Each element of the output vector is calculated as a high-order polynomial of all 6 input elements. The whole thing is a map that I want to iterate. I plan to evaluate each of the 6 functions in a separate thread (the input vector of course is the same for all six) and then put the results together in a Vector, to be used as input for the next iteration.

Facing difficulty I finally wrote myself a little toy program to check out the basic mechanism. Here it is:

                "Maple Initialization loaded..."
f:=x -> 1+x^2;
                        f := x -> 1 + x

for i from 1 to 10 do
end do:

So far so good; even the output (not shown) makes sense. BUT: as I increase the number of iterations in the loop, the memory allocation goes up fast, and I hit a point at about 40 iterations where the whole process locks up and the program never ends, cannot even be stopped (at least for 100 iterations), forcing me to abort the whole thing. I have evidence that Maple allocates vast amounts of memory which finally chokes the whole thing (on a 16 GB-RAM machine).

Anyone have any idea what I am doing wrong? I realize the above example does not provide benefits; in the real example there will be 6 Creates and the loop will Wait for all of these to finish.

I'd really like to get this to work as each function can take quite some time and I do expect at least some speed-up from parallelizing this (even after overhead).

This is on Maple 2015 on Mac OS X 10.10.5 with 16 GB of RAM. I should mention that I set UseHardwareFlots:=true in my .mapleinit file.



Hi!I am running some grid computations and I found that I could speed up my computations if my nodes could share some partial results. It seems that Grid:-Send and Grid:-Receive is almost perfect. The problem is that Grid:-Receive blocks the computations where I cannot ensure that a message will ever be send. I've tried to run Grid:-Receive on a thread in an possible infinite loop but it still blocks.

Some pieces of code below:

  while eval(stopValue) do
    SigContainer := eval(SigContainer) union {convert(Grid:-Receive(),string)};
  end do;
end proc:

SendMessage:=proc(message::string, id::integer)
  Threads[Seq](proc(i) if i <> id then Grid:-Send(i,message) end if end proc,i=0..Grid:-NumNodes()-1);
end proc:

In the main procedure run on a node I have







stopValue := false;


Do you have any suggestions how to solve my problem?

I a working with circuits, and was wondering whether or not it might be possible to shorten the proces of calculating parallel resistors. My idea is that using some symbol, such as || would find the equivalent resistor.

My idea is based on the fact that CrossProduct can also be done using &x command. Like so.

CrossProduct(a,b) = a &x b


So for resistors it would look something like:

Parallel(a,b) = a || b


For those interested the function for parallel resistors would be:

Parallel := (a,b) -> 1/(1/a+1/b);






I have bought maple18 student edition. I want to learn GPU programming through Maple. Please suggest how to do this. I have a notebook with i7 processor and NVIDIA geforce 750m graphics. I want to solve system of algebraic equations, integral equations etc in parallel using GPUs.


Hello, Maple wizards.

I have a problem with Tasks for parallel computations. In each task my programm should execute this command:


"A" and "B" are Arrays (1..m). "m" is integer. I have 8 tasks. Each task is a loop ("for i from 1 to n do..." n is integer), where my command is executing. "A" and "B" are local for each task. In this case each task should execute my command n times.

So, I obtain this:

"Error, (in SignalProcessing:-Engine:-DFT) attempting to assign to `FwdDFT` which is protected"

What is it? In Maple Help I read that ">SignalProcessing:-DFT" is Thread-Safe Function.


Dear all;


I need a help in this question.

u(x,y,t) my solution of PDE. x,y space, and t=time.

In the case without t. .i.e. u(x,y). Here is a visualization of the lattice u(x_i,y_j). i=1..3, anf j=1..3.  Please try this example, it's working. 

my question, if i would like to add a third variable t, i.e.  and get u(x_i,y_j,t_k)  on each points. I would like to show the lattice in (x,y) plan for each t_k. I Think I will get many parallel lattice. 

Please can some one, modify this code to get the parallel lattice. Thanks.



L := 'L':
N := 'N':
g := 'g':
Z := i -> -L+2*L/(N+1)*i;
x[0] = Z(0),x[N+1] = Z(N+1),y[0] = Z(0),y[N+1] = Z(N+1);


N := 4;
L := 1;
r := L/(N+1)/4;
ngon := (n,x,y,r,phi) -> [seq([x+r*cos(2*Pi*i/n+phi), y+r*sin(2*Pi*i/n+phi)], i = 1 .. n)]:
p[1] := display([seq(polygonplot(ngon(4,Z(0),Z(j),r,Pi/2),color=magenta),j=0..N+1),













If i use expression with function add() it runs normaly, but if I use expression with Threads:-Add (parallel implementation) it causes error "Error, continuation task already created for the current task" or "Kernel connection has been lost"


Array(1 .. N,1 .. 1/2*N-NR-1,(i, m) -> evalf(Add(cosArr2[modp(k*i,N)]/kl[k],k = 1 .. NR+m-1)+Add(cosArr2[modp(k*i,N)]*alpha[k],k = NR+m .. 1/2*N)))


What am I doing wrong? Can I use two Add in one evalf?

This post is an index page for reading the Parallel Programming blog posts.

Hello, everyone. I have some problem with multithreaded calculation. I just need calculate eigenvalues of matrix m at various parameters (and then export to a file) using advantages of the parallelizing. The following code works but in serial way


restart: with(LinearAlgebra):

m:=ImportMatrix(cat(currentdir(),"m.txt")): # here is matrix m.txt




local u,i,j,nmc:



for i from 2 to op([1,1],u) do


end do:

for i from 1 to op([1,1],u) do

nmc:=sort(Eigenvalues(m*u[i,1], output='list')):

for j from 2 to op([1,2],u) do


end do:

writedata[APPEND](cat(currentdir(),"u_",convert(k2,string),".txt"), [convert(Re(u[i]),list)]):


end do:

return finished:

end proc:



Start(ArrayTools[Concatenate], 2, Task=[prc,1,20], Task=[prc,20+step,40]);



The Start(ArrayTools[Concatenate], 2, Task=[prc,1,20], Task=[prc,20+step,40]) function makes two tasks of calculation at the parameter ranges of 1-20 and 21-40. But in this case Start spends twice more time than simply prc(20+step,40). How to realize a multithreaded calculation?

By the way I don't need to use a Concatenate function in Start but without any procedure Start doesn't work.

I've found the following project:

It is a very cheap but impressive computer ( 64-cores, they say it gives about 90 GFLOPS of computing power). The problem is the very limited amount of memory (1GB). See: for specifications.

Now my question is: do you think Maple will run on this machine (acoording to the site it will run Ubuntu) and if so then does it make sense to try it given the small amount of memory it has? Or in another words: do there exist problems that could be solved by Maple on this powerful machine and that cannot be solved on a regular machine with let's say 4GB of RAM?

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