In general I broadly agree with this approach, some specific comments below
> On 2 Oct 2017, at 2:11 am, Chris Marshall <[email protected]> wrote:
>>
>
> There are papers covering COS and its
> features and implementation at
>
> https://github.com/CObjectSystem/COS/tree/master/doc
> <https://github.com/CObjectSystem/COS/tree/master/doc>
What does COS offer that C++ and Obj-C do not?
>
>> In designing PDLNG one has to clear discuss and decide ‘what is it for’ ? I
>> think it is fairly obvious that the scipy ecosystem has taken over the
>> world, it has passed a critical mass in the last 3 years, and one must view
>> it in that context [confession: I use scipy, I have too. All my students and
>> collaborators do!].
>>
>> There could be multiple goals:
>>
>> - keep existing PDL code working for as long as possible? [this is a very
>> conservative goal; on the other hand without refresh there will be bitrot as
>> operating systems update]
>
> PDL 2.x is already in stable/bitrot-prevention mode.
Sure, but I was thinking more of the ten year horizon. e.g. when perl6 takes
over is it total-rewrite or die? There may not be legacy computers to run old
PDLs on!
>
>> - to be able to do all the things that scipy does [graphics, ML libraries,
>> jupyter, etc.] but using Perl syntax? [this can be way more efficient and
>> flexible, but may not be enough to justify a major effort. Unless there is a
>> clever way to plug-and-play the ecosystem? I certainly would be very happy
>> if I could write PDL code and call matplotlib in a jupyter notebook]
>
> One goal for the next generation PDL was to be able to
> have it callable from any language with a C FFI capability
> so that I could be language agnostic and still have PDL
> computing capabilities.
Then the trick is to define what is meant by ‘PDL computing capabilities’. Is
it the threading for example?
>
>> - to be able to do something better and new c.f. julia/python/R? [Ambitious.
>> What?]
>
> As I mentioned already, Julia maps very well into the new data
> language features I was wanting for PDL Next Generation:
> - you can call Python including NumPy and matplotlib from julia
> - JIT compiling is already there
> - I saw data frame support for julia
> - iJulia Jupiter notebooks already done (tutorials for julia are written in
> them)
> - julia has a friendly matlab-ish syntax and language
Then what is missing?
>
>> A related question would be where does Perl6 fit in to this? [sigh. If you
>> ask me Perl6 killed Perl.]
>
> Between python/numpy, R, and now julia, it seems
> clear to me thatperl is not the language most
> people look at for scientific and datacomputation.
> And, to be honest, the part about the Perl Data
> Language that I liked was the *Data Language* and
> not specificallyperl which happened to be the
> language I was using at the time.
Sure. But again we need to identify what it is we need to preserve here under
‘Data Language’. I am greatly interested in your opinion on this? More JIT type
compilation was one thing I think you want.
>
> My goals might now be specified as implementing
> X-DL whereall the nice data language features
> as are found in PDL andnow many languages can
> be accessed from other languageswhich would
> allow me to work on scientific computations
> and collaborate with colleagues independent of
> our individuallanguage preferences.
>
> Frankly, Julia as as Data Language minus Julia
> the languageand syntax is pretty much exactly
> the features I had hopedfor PDL Next Generation.
> Maybe thinking of the goals forX-DL from this
> point of view is a better way to see next
> generation DL capabilities.
>
> I plan to look at Julia more. If there were a
> cygwin Julia implementation (not a win32
> cross-compiled one) this would be even more
> compelling for my work flow use case.
>
> C
Glad to here it. My own cursory look at Julia was very encouraging!
Karl
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