It is weird that it happens as you de-select benchmarks. Does it happen with non-beta browsers? 2010/12/21 Dima Tisnek <dimaqq@gmail.com>:
Yes it does grind ff 4b7 to an almost halt, little cpu usage, reasonable memory size and constant disk activity for several minutes, very weird... So far, the difference between browsers is so large that I doubt it's dependent on data. Also it seems to tirgger as I remove columns progressively, thus new zero values should not appear, right?
I'll invesitage some more...
On 21 December 2010 01:06, Miquel Torres <tobami@googlemail.com> wrote:
Hi Dima,
another temp problem with speed pypy is that it's terrubly slow in ff beta. it also occasionally grinds in stable ff and opera, but I guess this can be forgiven for the sake of simplicity / developer effort.
Well, speed.pypy is actually fast in all modern browsers. The problem you are referring to is probably caused by a bug in the javascript plotting library (jqPplot) that is triggered in the comparison view when there are some results with 0 values. It only appears for some plot types, but it is very annoying because it grinds the browser to a halt like you say. Is that what you meant?
We are looking into it, and will fix that library if necessary.
Cheers, Miquel
2010/12/21 Dima Tisnek <dimaqq@gmail.com>:
On 20 December 2010 19:21, William ML Leslie <william.leslie.ttg@gmail.com> wrote:
On 21 December 2010 11:59, Dima Tisnek <dimaqq@gmail.com> wrote:
More visibility for performance achievements would do good too.
Where are pypy's performance achievements *not* visible, but should be?
for example http://shootout.alioth.debian.org/ doesn't say which pypy version is used, what options, doesn't have performance figures for multithreaded/multicore
also benchmarks are kinda small, most of them are not docuemented, and I couldn't find any info if the same python code was used for cpython and pypy (both shootout and speed pypy) or interpreter-specific verions were used, that is each tweaked for best performance given the known tradeoffs for each implementation.further the most standard benchmarks, pystone, etc. completely ignore the fact that real world programs are large and only a few small paths are execured often.
another temp problem with speed pypy is that it's terrubly slow in ff beta. it also occasionally grinds in stable ff and opera, but I guess this can be forgiven for the sake of simplicity / developer effort.
if you google for 'python performance' you don't get a single link to pypy on the first page, as a matter of fact, codespeak is poorly indexed, it took me quite some time to get some of my questions answered with a search. also if you look up 'pypy gc' you get a page on codespeak, but to interpret what the data actually means is so far beyond me.
a good overview is found in the mainling list http://codespeak.net/pipermail/pypy-dev/2010q1/005757.html then again slowspitfire and spambayes bits are outdated by now.
the definitive good thing about pypy is that it's much easier to find out about its inner workings than that of cpython!
hopefully a bit more of end-user stuff get known. let's call it pypy public outreach (feature request)
Sidetracking... one day when pypy jit/gc/etc are all worked out, how hard would it be to use same techniques and most of backends for some unrelated language that doesn't have jit yet, e.g. php?
You know that pypy already has implementations of other languages, right - Scheme, Javascript, Prolog, IO and smallTalk? They aren't integrated with the translated pypy-c, but they show that it is not too difficult to write a runtime for any dynamic language you choose.
Oh I didn't know there were so many, and I mistakenly though that js was a target, not implmented langauge. In any case I read somewhere that js support was retired...
And how hard would it be to marry two dynamic languages, so that modules from one could be used in the other? Or that modules written in rpython could be used in several langs?
It's in the "interesting problems" bucket, and the effort required depends on the level of integration between languages you want. There are several projects already attempting to do decent integration between several languages, besides the approach used on the JVM, there are also GNU Guile, Racket, and Parrot, among others. It might be worth waiting to see how these different projects pan out, before spending a bunch of effort just to be an also-ran in the multi-language runtime market.
However, implementing more languages in rpython has the side-effect of propagating the l * o * p problem: it introduces more and more implementations that then have to be maintained, so good cross-language integration probably belongs /outside/ pypy itself, so existing runtimes can hook into it.
Makes perfect sense, after all any given other language hardly has the same data model as python.
But it would be an interesting experiment (to marry the various interpreters pypy ships with), if you wanted to try it.
My two cents.
-- William Leslie
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