> I don't want to interrupt the flow but I'M feeling cheeky. One word can > solve everything "Fortran". There I said it.
Of course, but you forgot "now get off my lawn" -- Doug > > Jeff > > > On Thu, Mar 14, 2019, 17:03 Douglas Eadline <deadl...@eadline.org> wrote: > >> >> > Then given we are reaching these limitations how come we donââ¬â¢t >> integrate >> > certain things from the HPC world into every day computing so to >> speak. >> >> Scalable/parallel computing is hard and hard costs time and money. >> In HPC the performance often justifies the means, in other >> sectors the cost must justify the means. >> >> HPC has traditionally trickled down in to other sectors. However, >> many or the HPC problem types are not traditional computing >> problems. This situation is changing a bit with things >> like Hadoop/Spark/Tensor Flow >> >> -- >> Doug >> >> >> > >> > On 14/03/2019, 19:14, "Douglas Eadline" <deadl...@eadline.org> >> wrote: >> > >> > >> > > Hi Douglas, >> > > >> > > Isnt there quantum computing being developed in terms of CPUs at >> > this >> > > point? >> > >> > QC is (theoretically) unreasonably good at some things at other >> > there may me classic algorithms that work better. As far as I >> know, >> > there has been no demonstration of "quantum >> > supremacy" where a quantum computer is shown >> > to be faster than a classical algorithm. >> > >> > Getting there, not there yet. >> > >> > BTW, if you want to know what is going on with QC >> > read Scott Aaronson's blog >> > >> > https://www.scottaaronson.com/blog/ >> > >> > I usually get through the first few paragraphs and >> > then whoosh over my scientific pay grade >> > >> > >> > > Also is it really about the speed any more rather then how >> > > optimized the code is to take advantage of the multiple cores >> that >> > a >> > > system has? >> > >> > That is because the clock rate increase slowed to a crawl. >> > Adding cores was a way to "offer" more performance, but introduced >> > the "multi-core tax." That is, programing for multi-core is >> > harder and costlier than a single core. Also, much >> > harder to optimize. In HPC we are lucky, we are used to >> > designing MPI codes that scale with more cores (no mater >> > where they live, same die, next socket, another server). >> > >> > Also, more cores usually means lower single core >> > frequency to fit into a given power envelope (die shrinks help >> > with this but based on everything I have read, we are about >> > at the end of the line) It also means lower absolute memory >> > BW per core although more memory channels help a bit. >> > >> > -- >> > Doug >> > >> > >> > > >> > > ïûÿOn 13/03/2019, 22:22, "Douglas Eadline" < >> deadl...@eadline.org> >> > wrote: >> > > >> > > >> > > I realize it is bad form to reply ones own post and >> > > I forgot to mention something. >> > > >> > > Basically the HW performance parade is getting harder >> > > to celebrate. Clock frequencies have been slowly >> > > increasing while cores are multiply rather quickly. >> > > Single core performance boosts are mostly coming >> > > from accelerators. Added to the fact that speculation >> > > technology when managed for security, slows things down. >> > > >> > > What this means, the focus on software performance >> > > and optimization is going to increase because we can just >> > > buy new hardware and improve things anymore. >> > > >> > > I believe languages like Julia can help with this situation. >> > > For a while. >> > > >> > > -- >> > > Doug >> > > >> > > >> Hi All, >> > > >> Basically I have sat down with my colleague and we have >> opted >> > to go >> > > down >> > > > the route of Julia with JuliaDB for this project. But here >> is >> > an >> > > > interesting thought that I have been pondering if Julia is >> an >> > up >> > > and >> > > > coming fast language to work with for large amounts of >> data >> > how >> > > will >> > > > that >> > > >> affect HPC and the way it is currently used and HPC >> systems >> > > created? >> > > > >> > > > >> > > > First, IMO good choice. >> > > > >> > > > Second a short list of actual conversations. >> > > > >> > > > 1) "This code is written in Fortran." I have been met with >> > > > puzzling looks when I say the the word "Fortran." Then it >> > > > comes, "... ancient language, why not port to modern ..." >> > > > If you are asking that question young Padawan you have >> > > > much to learn, maybe try web pages" >> > > > >> > > > 2) I'll just use Python because it works on my Laptop. >> > > > Later, "It will just run faster on a cluster, right?" >> > > > and "My little Python program is now kind-of big and has >> > > > become slow, should I use TensorFlow?" >> > > > >> > > > 3) <mcoy> >> > > > "Dammit Jim, I don't want to learn/write Fortran,C,C++ and >> > MPI. >> > > > I'm a (fill in domain specific scientific/technical >> > position)" >> > > > </mcoy> >> > > > >> > > > My reply,"I agree and wish there was a better answer to >> that >> > > question. >> > > > The computing industry has made great strides in HW with >> > > > multi-core, clusters etc. Software tools have always >> lagged >> > > > hardware. In the case of HPC it is a slow process and >> > > > in HPC the whole programming "thing" is not as "easy" as >> > > > it is in other sectors, warp drives and transporters >> > > > take a little extra effort. >> > > > >> > > > 4) Then I suggest Julia, "I invite you to try Julia. It is >> > > > easy to get started, fast, and can grow with you >> > application." >> > > > Then I might say, "In a way it is HPC BASIC, it you are >> old >> > > > enough you will understand what I mean by that." >> > > > >> > > > The question with languages like Julia (or Chapel, etc) >> is: >> > > > >> > > > "How much performance are you willing to give up for >> > > convenience?" >> > > > >> > > > The goal is to keep the programmer close to the problem at >> > hand >> > > > and away from the nuances of the underlying hardware. >> > Obviously >> > > > the more performance needed, the closer you need to get to >> > the >> > > hardware. >> > > > This decision goes beyond software tools, there are all >> kinds >> > > > of cost/benefits that need to be considered. And, then >> there >> > > > is IO ... >> > > > >> > > > -- >> > > > Doug >> > > > >> > > > >> > > > >> > > > >> > > > >> > > > >> > > > >> > > >> Regards, >> > > >> Jonathan >> > > >> -----Original Message----- >> > > >> From: Beowulf <beowulf-boun...@beowulf.org> On Behalf Of >> > Michael >> > > Di >> > > > Domenico >> > > >> Sent: 04 March 2019 17:39 >> > > >> Cc: Beowulf Mailing List <beowulf@beowulf.org> >> > > >> Subject: Re: [Beowulf] Large amounts of data to store and >> > process >> > > On >> > > > Mon, Mar 4, 2019 at 8:18 AM Jonathan Aquilina >> > > > <jaquil...@eagleeyet.net> >> > > >> wrote: >> > > >>> As previously mentioned we >> > donÃÆÃâÃââÃÆââ¬Å¡Ã¢ââ¬Å¡Ã¬ÃÆââ¬Å¡Ã¢ââ¬Å¾Ã¢t >> really need to have >> > > anything >> > > >>> indexed >> > > > so I am thinking flat files are the way to go my only >> concern >> > is >> > > the >> > > > performance of large flat files. >> > > >> potentially, there are many factors in the work flow that >> > > ultimately >> > > > influence the decision as others have pointed out. my >> flat >> > file >> > > example >> > > > is only one, where we just repeatable blow through the >> files. >> > > >>> Isnt that what HDFS is for to deal with large flat >> files. >> > > >> large is relative. 256GB file isn't "large" anymore. >> i've >> > pushed >> > > TB >> > > > files through hadoop and run the terabyte sort benchmark, >> and >> > yes it >> > > can >> > > > be done in minutes (time-scale), but you need an >> astounding >> > amount >> > > of >> > > > hardware to do it (the last benchmark paper i saw, it was >> > something >> > > 1000 >> > > > nodes). you can accomplish the same feat using less and >> less >> > > > complicated hardware/software >> > > >> and if your dev's are willing to adapt to the hadoop >> > ecosystem, you >> > > sunk >> > > > right off the dock. >> > > >> to get a more targeted answer from the numerous smart >> people >> > on >> > > the >> > > > list, >> > > >> you'd need to open up the app and workflow to us. >> there's >> > just too >> > > many >> > > > variables _______________________________________________ >> > > >> Beowulf mailing list, Beowulf@beowulf.org sponsored by >> > Penguin >> > > Computing >> > > > To change your subscription (digest mode or unsubscribe) >> > visit >> > > >> http://www.beowulf.org/mailman/listinfo/beowulf >> > > >> _______________________________________________ >> > > >> Beowulf mailing list, Beowulf@beowulf.org sponsored by >> > Penguin >> > > Computing >> > > > To change your subscription (digest mode or unsubscribe) >> > visit >> > > >> http://www.beowulf.org/mailman/listinfo/beowulf >> > > > >> > > > >> > > > -- >> > > > Doug >> > > > >> > > > >> > > > >> > > > >> > > > _______________________________________________ >> > > > Beowulf mailing list, Beowulf@beowulf.org sponsored by >> > Penguin >> > > Computing >> > > > To change your subscription (digest mode or unsubscribe) >> > visit >> > > > https://beowulf.org/cgi-bin/mailman/listinfo/beowulf >> > > > >> > > >> > > >> > > -- >> > > Doug >> > > >> > > >> > > >> > > >> > >> > >> > -- >> > Doug >> > >> > >> > >> > >> >> >> -- >> Doug >> >> _______________________________________________ >> Beowulf mailing list, Beowulf@beowulf.org sponsored by Penguin Computing >> To change your subscription (digest mode or unsubscribe) visit >> https://beowulf.org/cgi-bin/mailman/listinfo/beowulf >> > -- Doug _______________________________________________ Beowulf mailing list, Beowulf@beowulf.org sponsored by Penguin Computing To change your subscription (digest mode or unsubscribe) visit https://beowulf.org/cgi-bin/mailman/listinfo/beowulf
