Hi Nicolas,

On Mon, Jun 21, 2010 at 2:59 PM, Nicolas Cellier <
nicolas.cellier.aka.nice at gmail.com> wrote:

> 2010/6/21 Nicolas Cellier <nicolas.cellier.aka.nice at gmail.com>:
> > Compiler hack is available for Squeak 3.9 at
> > http://bugs.squeak.org/view.php?id=2918
> > Load the 3 .cs in indicated order.
> >
> > I will publish an update for latest trunk at the same place when I'll
> > have a bit of time...
> >
>
> Finally, I published a Compiler version for latest trunk in this
> SqueakSource repository
> Plus a hack or two to make external interface loadable in closure VM
> (there is an additional limitation in closure that is max number of
> block copied values<16)
>

I'm interested to see the code that exceeds this limitation.  Hopefully
it'll be temporary, but it'll take a bytecode redesign to overcome, so I
can't fix this anytime soon.  Sorry it has bitten you!


> Sometimes, it gets a bit tricky to initialize Smallapack.
> I did something like:
>
> LapackMatrix initialize.
> LapackMatrix allSubclasses do: [:e | [e initializeClassInstVars] ifError:
> []].
>
> Nicolas
>
> > Then the latest Smallapack code is at
> > http://www.squeaksource.com/Smallapack.html
> >
> > If you are on linux, you'd better use a relatively new VM correcting
> > http://bugs.squeak.org/view.php?id=3929
> >
> > Nicolas
> >
> >
> > 2010/6/21 arul selvan <arul.selvan at gmail.com>:
> >> nicolas,
> >>
> >> i will be interested to test if a port for squeak is available
> >>
> >> arul
> >>
> >>
> >> On Mon, Jun 21, 2010 at 12:41 PM, Nicolas Cellier
> >> <nicolas.cellier.aka.nice at gmail.com> wrote:
> >>> I started Smallapack for this purpose.
> >>> Smallapack interfaces BLAS+LAPACK thru FFI.
> >>> Very much like numpy...
> >>>
> >>> Smallapack works quite well in VW and Dolphin...
> >>> (In fact it did work very well since 1990 with st80 user primitives...)
> >>> ...Unfirtunately not so in Squeak (VM crach possibly).
> >>>
> >>> I'd like to put more time in it, but so far there has not been so much
> interest.
> >>>
> >>> Nicolas
> >>>
> >>> 2010/6/21 Jimmie Houchin <jdev at cyberhaus.us>:
> >>>> On 6/20/2010 10:41 AM, Lawson English wrote:
> >>>>>
> >>>>> On 6/20/10 6:08 AM, Nicolas Cellier wrote:
> >>>>>>
> >>>>>> 2010/6/20 Michael Haupt<mhaupt at gmail.com>:
> >>>>>>>
> >>>>>>> Hi Nicolas,
> >>>>>>>
> >>>>>>> On Sun, Jun 20, 2010 at 11:17 AM, Nicolas Cellier
> >>>>>>> <nicolas.cellier.aka.nice at gmail.com>  wrote:
> >>>>>>>>
> >>>>>>>> About 8) :  True, every single operation results in memory
> allocation
> >>>>>>>> / garbage collection, a burden for number crunching.
> >>>>>>>
> >>>>>>> really?
> >>>>>>>
> >>>>>>> There is this nice book by Didier Besset called "Object-Oriented
> >>>>>>> Implementation of Numerical Methods. An Introduction with Java and
> >>>>>>> Smalltalk.: An Introduction with Java and Smalltalk". It can't be
> >>>>>>> *that* bad. :-)
> >>>>>>
> >>>>>> Agree, "not worse than Matlab" was the meaning of my message.
> >>>>>>>>
> >>>>>>>> My own answer was: use C/FORTRAN for optimized number crunching
> >>>>>>>> functions. Use Smalltalk for any higher level/GUI function (via
> >>>>>>>> DLLCC/FFI). We may have more than 1 hammer in your toolset!
> >>>>>>>
> >>>>>>> With GPU connectivity things emerging, number crunching might even
> be
> >>>>>>> an interesting area for Smalltalk.
> >>>>>>>
> >>>>>>> Best,
> >>>>>>> Michael
> >>>>>>
> >>>>>> Yes, this falls in vectorizing the operations.
> >>>>>> But I would go for a GPU-BLAS implementation available to any
> language
> >>>>>> (Smalltalk and C as well).
> >>>>>>
> >>>>>> Nicolas
> >>>>>
> >>>>> How many parallel squeak processes would be required to = the speed
> of one
> >>>>> native library for arbitrary precision math, or for other math
> intensive
> >>>>> purposes?
> >>>>>
> >>>>> Lawson
> >>>>
> >>>> Hello,
> >>>>
> >>>> I would love to be using Squeak for my financial application.
> Numerical
> >>>> performance isn't currently what is stopping me. My problem is that I
> >>>> require interfacing with a Windows COM dll and in a future version
> with a
> >>>> Java library. Hopefully at some point I will be able to port to
> Squeak. I
> >>>> would much prefer it to using Python, which is what I am currently
> using.
> >>>>
> >>>> I didn't even know Squeak was in the running until I discovered the
> Matrix
> >>>> class. And for what I need to do it performs reasonably adequately.
> However
> >>>> Squeak does not to my knowledge have a comprehensive collection of
> >>>> mathematics methods to be able to be applied to a variety of data.
> Currently
> >>>> I am using Python and Numpy which has a nicely optimized
> >>>> Mathematics/Scientific set of functions using optimized C/Fortran
> libraries.
> >>>> I would love to see Squeak compete in this area. In fact the Numpy
> people
> >>>> are currently refactoring the library to turn it into a C library
> usable by
> >>>> other languages.
> >>>>
> >>>> Here is some samples from my experimentation.
> >>>>
> >>>> Some of what I am doing is doing rolling calculations over my dataset.
> >>>>
> >>>> dataset is one weeks worth of OHLC data of a currency pair.
> >>>>
> >>>> In Squeak I have.
> >>>>
> >>>> ttr := [
> >>>>  1 to: ((m rowCount) -500) do: [:i || row rowSum rowMax rowMin
> rowMedian
> >>>> rowAverage |
> >>>>  row := (m atRows: i to: (499+i) columns: 5 to: 5).
> >>>>  rowSum := row sum.
> >>>>  rowMax := row max.
> >>>>  rowMin := row min.
> >>>>  rowMedian := row median.
> >>>>  rowAverage := row average.
> >>>>  omd add: {rowSum . rowMax . rowMin . rowMedian . rowAverage}]]
> timeToRun.
> >>>>
> >>>> Squeak:  17 seconds,  with Cog 4.2 seconds  (nice work guys
> >>>> (Eliot/Teleplace)
> >>>>
> >>>> In Python/Numpy I have.
> >>>>
> >>>> import numpy as np
> >>>> def speedtest(array,omd):
> >>>>    t1 = time.time()
> >>>>    for i in range(0, (len(a)-500)):
> >>>>        rowmax = np.max(a['bidclose'][i:i+500])
> >>>>        rowmin = np.min(a['bidclose'][i:i+500])
> >>>>        rowsum = np.sum(a['bidclose'][i:i+500])
> >>>>        rowmedian = np.median(a['bidclose'][i:i+500])
> >>>>        rowmean = np.mean(a['bidclose'][i:i+500])
> >>>>        omd.append((rowsum, rowmax, rowmin, rowmedian, rowmean))
> >>>>    return time.time()-t1
> >>>>
> >>>> Python:  .7 seconds
> >>>>
> >>>> Python/Numpy performs well, is reasonably nice to work with. But I
> would
> >>>> give up the performance to be able to use Squeak. The live environment
> and
> >>>> debugging would be invaluable for experimentation.
> >>>>
> >>>> Hopefully this will give you some idea.
> >>>>
> >>>> Jimmie
> >>>>
> >>>>
> >>>
> >>>
> >>
> >>
> >
>
>
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