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: 103376,1a44c40a66c293f3 X-Google-Thread: 1089ad,7e78f469a06e6516 X-Google-Attributes: gid103376,gid1089ad,public X-Google-Language: ENGLISH,ASCII Path: g2news2.google.com!news3.google.com!border1.nntp.dca.giganews.com!nntp.giganews.com!newsfeed00.sul.t-online.de!t-online.de!tiscali!newsfeed1.ip.tiscali.net!proxad.net!fdn.fr!news.wanadoo.fr!news.wanadoo.fr!not-for-mail Message-ID: <45E9B032.60502@obry.net> Date: Sat, 03 Mar 2007 18:28:18 +0100 From: Pascal Obry Organization: Home - http://www.obry.net User-Agent: Thunderbird 2.0b2 (Windows/20070116) MIME-Version: 1.0 Newsgroups: comp.lang.ada,comp.lang.vhdl To: "Dr. Adrian Wrigley" Subject: Re: Embedded languages based on early Ada (from "Re: Preferred OS, processor family for running embedded Ada?") References: <113ls6wugt43q$.cwaeexcj166j$.dlg@40tude.net> <1i3drcyut9aaw.isde6utlv6iq.dlg@40tude.net> <1j0a3kevqhqal.riuhe88py2tq$.dlg@40tude.net> In-Reply-To: Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: 8bit NNTP-Posting-Date: 03 Mar 2007 18:28:34 CET NNTP-Posting-Host: 82.120.29.64 X-Trace: 1172942914 news.orange.fr 25948 82.120.29.64:1605 X-Complaints-To: abuse@orange.fr Xref: g2news2.google.com comp.lang.ada:9658 comp.lang.vhdl:7622 Date: 2007-03-03T18:28:34+01:00 List-Id: Dr. Adrian Wrigley a �crit : > Numerous algorithms in simulation are "embarrassingly parallel", > but this fact is completely and deliberately obscured from compilers. Not a big problem. If the algorithms are "embarrassingly parallel" then the jobs are fully independent. In this case that is quite simple, create as many tasks as you have of processors. No big deal. Each task will compute a specific job. Ada has no problem with "embarrassingly parallel" jobs. What I have not yet understood is that people are trying to solve, in all cases, the parallelism at the lowest lever. Trying to parallelize an algorithm in an "embarrassingly parallel" context is loosing precious time. Many real case simulations have billions of those algorithm to compute on multiple data, just create a set of task to compute in parallel multiple of those algorithm. Easier and as effective. In other words, what I'm saying is that in some cases ("embarrassingly parallel" computation is one of them) it is easier to do n computations in n tasks than n x (1 parallel computation in n tasks), and the overall performance is better. 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