From mboxrd@z Thu Jan 1 00:00:00 1970 X-Spam-Checker-Version: SpamAssassin 3.4.4 (2020-01-24) on polar.synack.me X-Spam-Level: X-Spam-Status: No, score=-1.9 required=5.0 tests=BAYES_00 autolearn=ham autolearn_force=no version=3.4.4 X-Google-Thread: 103376,c4cb2c432feebd9d X-Google-Thread: 1094ba,c4cb2c432feebd9d X-Google-Attributes: gid103376,gid1094ba,public X-Google-Language: ENGLISH,ASCII Path: g2news2.google.com!news4.google.com!news.glorb.com!proxad.net!fdn.fr!news.wanadoo.fr!news.wanadoo.fr!not-for-mail Message-ID: <44780167.4080106@obry.net> Date: Sat, 27 May 2006 09:36:07 +0200 From: Pascal Obry Organization: Home - http://www.obry.net User-Agent: Thunderbird 1.5 (Windows/20051201) MIME-Version: 1.0 Newsgroups: comp.lang.ada,comp.lang.fortran To: Nasser Abbasi Subject: Re: Ada vs Fortran for scientific applications References: In-Reply-To: Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: 8bit NNTP-Posting-Date: 27 May 2006 09:36:11 CEST NNTP-Posting-Host: 86.205.99.115 X-Trace: 1148715371 news.wanadoo.fr 21306 86.205.99.115:4505 X-Complaints-To: abuse@wanadoo.fr Xref: g2news2.google.com comp.lang.ada:4527 comp.lang.fortran:10342 Date: 2006-05-27T09:36:11+02:00 List-Id: Nasser Abbasi a �crit : > I also found this interesting note about some research done at IBM for > paralalizing Ada for numerical work > > "Parallelism in scientific applications can most often be found at the loop > level. Although Ada supports parallelism via the task construct, its > coarseness renders it unsuitable for this light-weight parallelism." And this is talking only about a small part of the total application. In some applications I know where OpenMP is used to do parallel computing the gain is 20% or 30%. Why ? Because most of the application is not doing vector computing! This is often only a small part of an application. The application needs to read data, prepare them, do some computation, eventually communicate with some other applications, do some more computations... write the data, do some 2D/3D display... At this level of parallelism Ada tasking is a really nice solution. The fork/join model of OpenMP is not that efficient and certainly not a general purpose model. We are not in a world of vector-oriented architecture and vectorizing compiler (Cray, Fujitsu) but in a multi-processor or dual-core cluster/grid. I'm not sure IBM would say the same thing today... Pascal. -- --|------------------------------------------------------ --| Pascal Obry Team-Ada Member --| 45, rue Gabriel Peri - 78114 Magny Les Hameaux FRANCE --|------------------------------------------------------ --| http://www.obry.net --| "The best way to travel is by means of imagination" --| --| gpg --keyserver wwwkeys.pgp.net --recv-key C1082595