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Parallel Conjugate gradient linear system solver
Ramine
6/30/2014 1:41:00 AM
Hello,
As you have noticed i have implemented my Parallel Conjugate gradient
linear system solver, here it is:
https://sites.google.com/site/aminer68/parallel-implementation-of-conjugate-gradient-linear-sys...
But as you will notice i am using arrays to implement it ,
but arrays do take too much memory even if the matrix is more
sparse, but i have decided to implement it like that with arrays,
so a matrix of 100000 by 1000000 elements will take around
64 Gbytes of memory, so you have to have a server with 32 Gbytes
of memory or more to be able to solve large industrial problems
with my parallel Parallel Conjugate gradient linear system solver.
To use much less memory i have to use linklists , but linklists
are not parallel freindly with my parallel algorithm, they will
be too CPU expensive , hence too slow, so this why i have decided
to keep using arrays in my parallel algorithm
Thank you,
Amine Moulay Ramdane.
1 Answer
Ramine
6/30/2014 1:43:00 AM
0
On 6/29/2014 6:41 PM, Ramine wrote:
>
> Hello,
>
> As you have noticed i have implemented my Parallel Conjugate gradient
> linear system solver, here it is:
>
>
>
https://sites.google.com/site/aminer68/parallel-implementation-of-conjugate-gradient-linear-sys...
>
>
>
> But as you will notice i am using arrays to implement it ,
> but arrays do take too much memory even if the matrix is more
> sparse, but i have decided to implement it like that with arrays,
> so a matrix of 100000 by 1000000 elements will take around
I mean a matrix of 100000 by 100000 elements
> 64 Gbytes of memory, so you have to have a server with 32 Gbytes
> of memory or more to be able to solve large industrial problems
> with my parallel Parallel Conjugate gradient linear system solver.
>
> To use much less memory i have to use linklists , but linklists
> are not parallel freindly with my parallel algorithm, they will
> be too CPU expensive , hence too slow, so this why i have decided
> to keep using arrays in my parallel algorithm
>
>
> Thank you,
> Amine Moulay Ramdane.
>
>
>
>
>
>
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