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From: Francois Berenger <francois.berenger@inria.fr>
To: 'OCaml Mailing List' <caml-list@inria.fr>
Cc: caml-list@inria.fr
Subject: [Caml-list] Re : Sklml first public release
Date: Sat, 1 Oct 2016 22:16:09 +0200 (CEST)	[thread overview]
Message-ID: <1413603362.6315173.1475352969328.JavaMail.zimbra@inria.fr> (raw)
In-Reply-To: <20160929161346.ABF4FE1A4F@yquem.inria.fr>

Hi,

Very cool and interesting work.

Can sklml be used to program GPUs?

I ´m a big fan of parmap; but I ´m ok to switch to anything high performance.

Also, is there an opam switch or something for sklml?

Thanks a lot for this alien technology,
Francois.

----- Pierre Weis <pierre.weis@inria.fr> a écrit :
>                    Easy coarse grain parallelization                    
> 
> We are glad to announce the availability of Sklml version 2.0+pl0.
> 
> What is Sklml?
> ==============
> 
> Sklml is a functional parallel skeleton compiler and programming system for OCaml programs.
> 
> The Sklml system is embedded into the OCaml programming language
> and inherits the good properties of this functional heritage: Sklml
> programs cannot go wrong (no bus error nor segmentation faults).
> 
> All Sklml programs may be run in two evaluation modes: parallel or
> sequential evaluation.
> 
> The Sklml system features another salient property: for any
> Sklml program the sequential and parallel evaluation modes always
> return the same result. In particular, the parallel evalution mode is
> deterministic and do not introduce nor hide any error (such as floating point
> rounding errors).
> 
> In Sklml, parallelization is explicit and uses high-level
> parallelization primitives for program parallel and data parallel usual
> programming situations.
> 
> Composing the parallelization primitives is a powerful way to define more
> complex or specialized parallelization schemes. For instance, the
> Sklml library features a 'domain' high-level function devoted to
> advanced scientific computing: indeed, the function 'mk_domain' provides a
> parallel implementation of the classical 'Domain Decomposition' method to
> solve Partial Differential Equations. Using the same methodology, advanced
> users can define powerful parallelization functions and tune Sklml
> to the specific domain at hand.
> 
> Where to get the Sklml code?
> ============================
> 
> The tarball is available here:
>     http://sklml.inria.fr/archive/sklml-2.0+pl0.tgz
> 
> Where to get more information?
> ==============================
> 
> The package home page is here:
>     http://sklml.inria.fr/
> 
> All constructive criticisms and propositions are warmly welcomed.
> 
> Enjoy.
> 
> Francois Clement <Francois.Clement@inria.fr>
> Pierre Weis <Pierre.Weis@inria.fr>
> 
> -- 
> Caml-list mailing list.  Subscription management and archives:
> https://sympa.inria.fr/sympa/arc/caml-list
> Beginner's list: http://groups.yahoo.com/group/ocaml_beginners
> Bug reports: http://caml.inria.fr/bin/caml-bugs


  reply	other threads:[~2016-10-01 20:16 UTC|newest]

Thread overview: 3+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2016-09-29 16:13 [Caml-list] " Pierre Weis
2016-10-01 20:16 ` Francois Berenger [this message]
2016-10-01 22:40 ` Oliver Bandel

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