Re: parallelization

[Gerhard Niklasch <nikl@mathematik.tu-muenchen.de>]

In response to:
> Message-ID: <21C10221747AD3118E9D00E0293851AA04307342@exmail20.usma.army.mil>
> From: "Mills, D. Dr.              MATH" <ad3943@exmail.usma.army.mil>
> To: pari-users@list.cr.yp.to
> Date: Wed, 4 Apr 2001 13:19:41 -0400 
> 
> I'm using PARI on a supercomputer, and am curious to know any programming
> "tricks" or "tips" to aid me in efficiently parallelizing my programs.

What kind of platform and operating system  (and compiler)?

You can always subdivide the computational tasks and run several
independent processes each on its own cpu.  I have been using
this approach many times over the years on a variety of problems.

Whether or not you can efficiently exploit any hardware vector
capabilities of your cpus will depend on how good your compiler
and optimizer are on PARI's inner loops.  Finding places where
suitable hints or pragmas could be added is likely to be a non-
trivial task...  Compiling for profiling and making measurements
may help to find out what parts of the code are exercised by
your programs.

libpari currently will not lend itself to multithreading within
one and the same process  (since the central data structures
are accessed through global variables which exist only once) --
not without very devious hacks involving dlopen() and private
symbol tables, which I'd hesitate to delve into.  (And good
multithread-hot malloc() implementations are a story in and
of themselves.  Hoard is an interesting one, see www.hoard.org.
But in the context of PARI, this would be very difficult to
exploit at present, unless the problem is structured in such
a way that you can have the main thread executing in libpari
and other threads doing other things which do not depend on
libpari in any way, with proper synchronization around any
shared data structure accesses.)

Hope this helps,
Gerhard