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Re: machine learning for loop unrolling

From: Maxim Kuvyrkov <mkuvyrkov at ispras dot ru>
To: Zdenek Dvorak <rakdver at kam dot mff dot cuni dot cz>
Cc: Stefan Ciobaca <stefan dot ciobaca at gmail dot com>, gcc at gcc dot gnu dot org
Date: Sat, 09 Jun 2007 11:14:21 +0400
Subject: Re: machine learning for loop unrolling
References: <165ddd80706080630y5579dc89u39867f649b18c72e@mail.gmail.com> <20070609000126.GA20280@kam.mff.cuni.cz>

Zdenek Dvorak wrote:

...

The number of parallel "computations" in loop.
The estimated latency of the critical path of loop.
The estimated cycle length of loop body.
The max. dependence height of computations.
The max. height of memory dependencies of computations.
The max. height of control dependencies of computations.
The average dependence height of computations.
The min. memory-to-memory loop-carried dependence.
The number of memory-to-memory dependencies.


This is a bit more difficult; I guess you could persuade scheduler to
give you this information, but I have no idea how exactly.  See
modulo-sched.c, it considers similar kind of information.

Stefan,

You can get a DDG for an acyclic graph (which one iteration of the loop is :) from sched-deps.c. From that DDG it should not be difficult to compute properties you want. If you want to get interloop properties, then take a look at ddg.c - modulo-sched.c uses it to build interloop dependencies.

--
Maxim

References:
- machine learning for loop unrolling
  - From: Stefan Ciobaca
- Re: machine learning for loop unrolling
  - From: Zdenek Dvorak

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