Services & Resources / Wolfram Forums
-----
 /
MathGroup Archive
2000
*January
*February
*March
*April
*May
*June
*July
*August
*September
*October
*November
*December
*Archive Index
*Ask about this page
*Print this page
*Give us feedback
*Sign up for the Wolfram Insider

MathGroup Archive 2000

[Date Index] [Thread Index] [Author Index]

Search the Archive

Re: Parallel programming.

  • To: mathgroup at smc.vnet.net
  • Subject: [mg22938] Re: Parallel programming.
  • From: Jens-Peer Kuska <kuska at informatik.uni-leipzig.de>
  • Date: Fri, 7 Apr 2000 02:54:25 -0400 (EDT)
  • Organization: Universitaet Leipzig
  • References: <8cha2f$975@smc.vnet.net>
  • Sender: owner-wri-mathgroup at wolfram.com

Hi,

it works fine. It is pure Mathematica and connects the Kernel via 
MathLink. To run it on a 4 CPU machine you need 4 kernel licenses.

We use it here with 10 site licenses on a Origin with 4 CPU's and
on a Linux Cluster.

The speed gain with Mathematica is large - on my test problems it was
easy
to obtain the "ideal" speed up of a factor N when N CPUs are used.

But it should be clear, that you waste CPU power and memory if you run
only numeric simulations. MathLink itself can be used to do this (with
out
a kernel license) and MPI is a free and (from my view point) more robust
protocol to do numeric's only. The main advantage in this case is,
you have the speed burst by the C-program *and* a possible speed gain
due
to parallel execution. For 4 CPU's this can mean 120 x faster with C &&
parallel computing instead of a factor of 4 by the parallel computing
toolkit
alone.

The parallel tookit implements a simple Master/Worker model and you will
need some additional programming to setup other models or topologies.

For simple matrix problems I can't recomment any parallel programming.
The overhead (by shared memory implementation as well as for distributed
memory applications) is too huge. The only pure matrix operation that
look
good are LU solutions or iterative solvers. But especial LU
factorisations
will be a bit hard to implement (pivoting).

Only a few parallel algorithms for symbolic computing are known -- but
this is the topic where the parallel toolkit on the top of Mathematica
show the true power.

You can have two examples of a parallel Runge-Kutta code for 2 CPU's
as pure C/MathLink version and as Mathematica/Parallel Computing Tookit
version. The pure C/MathLink version is called form Mathematica and send
the results back to one kernel when the parallel computation  is
finished.

Hope that helps
  Jens
"Dr. David Kirkby" wrote:
> 
> I use Mathematica at work on several fast machines, and at home on a
> rather old Sun SPARC 20. The latter machine does have the advantage of
> multiple CPUs, although none are exactly fast (quad 125 MHz
> HyperSPARCs). Mathematica does not use these multiple CPUs, but I see
> there is a parallel computing toolkit available now.
> http://www.wolfram.com/news/pct.html
> Does anyone know how this works ? I can't justify the cost for a home
> machine, but given it is all written in Mathematica code (I believe), it
> would seem that it would not take a lot of effort to implement some of
> this, for simple matrix problems. My licence allows me to run multiple
> kernels on this quad CPU sparc, suggesting it would be possible to use
> the power of my 4 cpus.
> 
> Any suggestions or thoughts ?
>


  • Prev by Date: Re: Mathematica NDSolve max number of grid points error
  • Next by Date: Fast List Manipulation & more
  • Previous by thread: Re: Parallel programming.
  • Next by thread: Re: Parallel programming.