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,FREEMAIL_FROM autolearn=unavailable autolearn_force=no version=3.4.4 X-Received: by 10.107.24.67 with SMTP id 64mr13062668ioy.87.1507132059744; Wed, 04 Oct 2017 08:47:39 -0700 (PDT) X-Received: by 10.157.39.194 with SMTP id c60mr310269otb.6.1507132059715; Wed, 04 Oct 2017 08:47:39 -0700 (PDT) Path: eternal-september.org!reader01.eternal-september.org!reader02.eternal-september.org!news.eternal-september.org!feeder.eternal-september.org!border1.nntp.ams1.giganews.com!nntp.giganews.com!peer01.ams1!peer.ams1.xlned.com!news.xlned.com!peer03.am4!peer.am4.highwinds-media.com!peer03.iad!feed-me.highwinds-media.com!news.highwinds-media.com!v62no4121950itd.0!news-out.google.com!p6ni5245itp.0!nntp.google.com!v62no4124337itd.0!postnews.google.com!glegroupsg2000goo.googlegroups.com!not-for-mail Newsgroups: comp.lang.ada Date: Wed, 4 Oct 2017 08:47:39 -0700 (PDT) In-Reply-To: Complaints-To: groups-abuse@google.com Injection-Info: glegroupsg2000goo.googlegroups.com; posting-host=57.79.21.10; posting-account=gRqrnQkAAAAC_02ynnhqGk1VRQlve6ZG NNTP-Posting-Host: 57.79.21.10 References: User-Agent: G2/1.0 MIME-Version: 1.0 Message-ID: Subject: Re: Why does Ada compile slower than Python? From: gautier_niouzes@hotmail.com Injection-Date: Wed, 04 Oct 2017 15:47:39 +0000 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable X-Received-Bytes: 2060 X-Received-Body-CRC: 3974353788 Xref: news.eternal-september.org comp.lang.ada:48349 Date: 2017-10-04T08:47:39-07:00 List-Id: Fortunately, with GNAT, the slow build time is well rewarded by performance= . I just have the following real case today at my job: A certain number-crunching job is a big bottleneck since years. It has been= developed as a SQL stored procedure. Then someone has made a Python versio= n (program compiled into an executable). Independently I've made an Ada ver= sion. All three programs produce the same result. SQL : 12 hours run time - weeks of development work Python : 3 hours run time - weeks of development work Ada : 27 minutes run time - 3 days of development work. Now the "clou": most of the run time is actually spent loading data via a S= QL select instruction. The actual number-crunching in Ada takes 24 *seconds= * in total!... Since the loading of data is a "fixed cost" (+/- the same wh= atever the implementation language) I let as an exercise to figure out the = speedup factor of the computation side :-). G.