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D - Psycho about Performance

reply Mark Evans <Mark_member pathlink.com> writes:
Here is an interesting result from a budding Ph.D. in computer science who works
with Python, a high-level language that is (a) weakly typed and (b) notoriously
slow.  He shows how to execute such code with nearly C levels of performance.
This is a working product, not an idea.  It shows at least two things that I
have said before, (1) we have much to learn from experts, and (2) high level
features do not need to spell "slow."  Read his remarks below.

Walter, the code is MIT licensed on SourceForge.  Plagiarize shamelessly!  -M

http://psyco.sourceforge.net/introduction.html

Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like
Java's, that emit machine code on the fly instead of interpreting your Python
program step by step. The result is that your unmodified Python programs run
faster.  [D could do something similar to support high-level features. -M.]

The actual performance gains can be very large. For common code, expect at least
a 2x speed-up, more typically 4x. But where Psyco shines is when running
algorithmical code --- these are the first pieces of code that you would
consider rewriting in C for performance. If you are in this situation, consider
using Psyco instead! You might get 10x to 100x speed-ups. It is theoretically
possible to actually speed up this kind of code up to the performance of C
itself.

My goal in programming Psyco is to contribute to reduce the following wide gap
between academic computer science and industrial programming tools.

While the former develops a number of programming languages with very cool
semantics and features, the latter stick with low-level languages principally
for performance reasons, on the ground that the higher the level of a language,
the slower it is. Althought clearly justified in practice, this belief is
theoretically false, and even completely inverted --- for large, evolving
systems like a whole operating system and its applications, high-level
programming can deliver much higher performances.

The new class of languages called "dynamic scripting languages", of which Python
is an example, is semantically close to long-studied languages like Lisp. The
constrains behind their designs are however different: some high-level languages
can be relatively well statically compiled, we can do some type inference, and
so on, whereas with Python it is much harder --- the design goal was different.
We now have powerful machines to stick with interpretation for a number of
applications. This, of course, contributes to the common belief that high-level
languages are terribly slow.

Psyco is both an academic and an industrial project. It is an academic
experiment testing some new techniques in the field of on-line specialization.
It develops an industrially useful performance benefit for Python.
Nov 15 2002
next sibling parent reply Mark Evans <Mark_member pathlink.com> writes:
Mark Evans says...

Here is an interesting result from a budding Ph.D. in computer science


(correction, mathematics; but his software is still sooo cooooooolllll.....he is
an expert in my book)
Nov 15 2002
parent reply johnwhited hotmail.com writes:
Several reviews I've read say Psycho takes way too much memorize to use and in
most cases (non-algorithmetic) is not even a factor of 2 times faster. 

This article is a pretty glowing review. 

In article <ar4qre$2uii$1 digitaldaemon.com>, Mark Evans says...

Mark Evans says...

Here is an interesting result from a budding Ph.D. in computer science


(correction, mathematics; but his software is still sooo cooooooolllll.....he is
an expert in my book)
Nov 16 2002
parent reply Juanjo =?ISO-8859-1?Q?=C1lvarez?= <juanjux yahoo.es> writes:
johnwhited hotmail.com wrote:


 Several reviews I've read say Psycho takes way too much memorize to use
 and in most cases (non-algorithmetic) is not even a factor of 2 times
 faster.


I can tell you that I've sucessfully used it to improve about a factor of 4 
a not specially algorithmetic program (a mail program), and that only 
psycompiling a few methods, now the entire code (altought I doubt I could 
gain much more performance psycompiling all).
Dec 02 2002
parent johnwhited hotmail.com writes:
I can tell you that I've sucessfully used it to improve about a factor of 4 
a not specially algorithmetic program (a mail program), and that only 
psycompiling a few methods, now the entire code (altought I doubt I could 
gain much more performance psycompiling all).


More than likely the amount of string manipulation you're doing benefits from
the JITing process. Anyhow, I'm just quoting what I read from a couple of
places reviewing the perf of this JITer.
Dec 02 2002
prev sibling next sibling parent "Walter" <walter digitalmars.com> writes:
Similar ideas have been around for a while, but I don't know anyone who's
gone very far implementing them.

"Mark Evans" <Mark_member pathlink.com> wrote in message
news:ar4gbu$2kpv$1 digitaldaemon.com...

 Here is an interesting result from a budding Ph.D. in computer science who


works

 with Python, a high-level language that is (a) weakly typed and (b)


notoriously

 slow.  He shows how to execute such code with nearly C levels of


performance.

 This is a working product, not an idea.  It shows at least two things that


I

 have said before, (1) we have much to learn from experts, and (2) high


level

 features do not need to spell "slow."  Read his remarks below.

 Walter, the code is MIT licensed on SourceForge.  Plagiarize


hamelessly!  -M

 http://psyco.sourceforge.net/introduction.html

 Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like
 Java's, that emit machine code on the fly instead of interpreting your


Python

 program step by step. The result is that your unmodified Python programs


run

 faster.  [D could do something similar to support high-level


features. -M.]

 The actual performance gains can be very large. For common code, expect at


least

 a 2x speed-up, more typically 4x. But where Psyco shines is when running
 algorithmical code --- these are the first pieces of code that you would
 consider rewriting in C for performance. If you are in this situation,


consider

 using Psyco instead! You might get 10x to 100x speed-ups. It is


theoretically

 possible to actually speed up this kind of code up to the performance of C
 itself.

 My goal in programming Psyco is to contribute to reduce the following wide


gap

 between academic computer science and industrial programming tools.

 While the former develops a number of programming languages with very cool
 semantics and features, the latter stick with low-level languages


principally

 for performance reasons, on the ground that the higher the level of a


language,

 the slower it is. Althought clearly justified in practice, this belief is
 theoretically false, and even completely inverted --- for large, evolving
 systems like a whole operating system and its applications, high-level
 programming can deliver much higher performances.

 The new class of languages called "dynamic scripting languages", of which


Python

 is an example, is semantically close to long-studied languages like Lisp.


The

 constrains behind their designs are however different: some high-level


languages

 can be relatively well statically compiled, we can do some type inference,


and

 so on, whereas with Python it is much harder --- the design goal was


different.

 We now have powerful machines to stick with interpretation for a number of
 applications. This, of course, contributes to the common belief that


high-level

 languages are terribly slow.

 Psyco is both an academic and an industrial project. It is an academic
 experiment testing some new techniques in the field of on-line


specialization.

 It develops an industrially useful performance benefit for Python.
Nov 16 2002
prev sibling parent Ilya Minkov <midiclub 8ung.at> writes:
I see you're interested in run-time specialiastion. Please read:

http://www.codeonthefly.com/academic.html

It also falls into my sphere of ineterests.

Much more inetersting for me is the runtime generation of numerical 
code. Imagine a music file, containing music score + playing algorithms 
+ data used by the algorithms. That would involve generating code on the 
fly.
Dec 29 2002