[Beowulf] Large amounts of data to store and process

[Jonathan Aquilina]

Hi Douglas,

Isnt there quantum computing being developed in terms of CPUs at this point? 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?

On 13/03/2019, 22:22, "Douglas Eadline" <deadline at 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-bounces at beowulf.org> On Behalf Of Michael Di
    > Domenico
    >> Sent: 04 March 2019 17:39
    >> Cc: Beowulf Mailing List <beowulf at beowulf.org>
    >> Subject: Re: [Beowulf] Large amounts of data to store and process On
    > Mon, Mar 4, 2019 at 8:18 AM Jonathan Aquilina
    > <jaquilina at eagleeyet.net>
    >> wrote:
    >>> As previously mentioned we don’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 _______________________________________________
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    > --
    > Doug
    >
    >
    >
    >
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    --
    Doug