good chemistry is complicated,
and a little bit messy -LW
Re^3: Perl 5 Optimizing Compiler, Part 4: LLVM Backend?by BrowserUk (Pope)
|on Aug 27, 2012 at 23:39 UTC||Need Help??|
I suspect that the performance of this hypothetical application would be determined almost exclusively by the performance of the hash-table code within the “guts,” such that time spent generating the parse-trees and then iterating through them would be negligible.
And I suspect that, once again, you haven't a clue what you are talking about. Have you ever bothered to look into hv.c?
Each Perl "opcode" has to deal with a complex variety of different possibilities.
With runtime compilation (or jit), it would be possible for 'simple hash' accesses/inserts/updates to bypass all of the myriad checks and balances that are required for the general case, which could yield significant gains in hash heavy code. Ditto for arrays. Ditto for strings. Ditto for numbers. (Do a super search for "use integer" to see some of the possibilities that can yeild.)
Then there is the simple fact that perl's subroutines/methods are -- even by interpreter standards -- very slow. (See: 488791 for a few salient facts about Perl's subcall performance.)
Much of this stems from the fact that the way the perl sources are structured, C compilers cannot easily optimise across compilation unit boundaries, because they mostly(*) do compile-time optimisations. However, there are a whole class of optimisations that can be done at either link-time or runtime, that would hugely benefit Perl code.
(*)MS compiler have the ability to do some link-time optimisations, and it would surprise me greatly if gcc doesn't have similar features. It would also surprise me if these have ever been enabled for teh compilation of Perl. They would need to be specifically tested on so many platforms, it would be very hard to do.
But, something like LLVM, can do link-time & runtime optimisations, because it (can) targets not specific processors, but a virtual processor (a "VM") which allows its optimiser to operate in that virtual environment. And only once the VM code has been optimised is it finally translated into processor specific machine code.That means you only need to test each optimiation (to the VM) once; and independently, the translation to each processor.
Not the combinatorial product of all optimisations on all processors.
What would these gains be worth? It is very hard to say, but if it gave 50% of the difference between (interpreted, non-JITed Java & perl running an recursive algorithm (Ackermann), that does a few simple additions (11 million times):
So 83.6 seconds for Perl, and 1.031 seconds for Java!
Perl's productivity and (1/2) Java's performance!
That would be something worth having for vast array of genomists, physicists, data miners et al.
Heck. It might even mean that hacks like mod_perl might become redundant; making a whole bunch of web monkeys happy. Moose might even become usable for interactive applications. Parse::RecDescent might be able to process document in real time rather than geological time. DateTime might be able to calculate deltas as they happen rather than historically.
There are three fundamental limitations on an interpreters performance:
Whilst Perl is faster than (native code) Python & Ruby, it sucks badly when compared to Java, LUA etc. And the reasons are:
In a nutshell, your "suspicions" are so out of touch with reality, and so founded upon little more than supposition, that they are valueless.
With the rise and rise of 'Social' network sites: 'Computers are making people easier to use everyday'
Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority".
In the absence of evidence, opinion is indistinguishable from prejudice.