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1 Introduction

Mercury provides a large number of compile-time options that enable or
disable optimisations to the code being generated.  It can be difficult
to determine which ones to apply, especially since different options may
work better with different programs or different inputs.  This program
attempts to find the optimal set of optimisation flags to be passed to
the compiler.  It works using a genetic algorithm; see the following
URLs for details on how genetic algorithms work:


The program is invoked using the gator script.  It may be useful (if
something goes wrong) to turn on the verbose flag and pipe the output to
a file:

                    ./gator -v 2>&1 | tee gator.out

The program stores its output in the directory generations.  Each generation
has its own subdirectory within generations.  For example, information about
the first generation is stored in generations/1.

There are a number of files in each of these directories.  The most
useful one is the file "ladder".  This file contains a table listing all
of the individuals in a generation.  Each individual is given a number,
between 1 and the size of its generation, in the first column of the
table.  The second column contains the "fitness" of an individual.  The
third column contains the "genotype" of an individual, which is the list
of compiler options that are passed to the compiler.

By default, gator is configured to optimise a simple "hello world"
program written in Mercury.  The following sections describe how to
configure gator to test different programs, including those using
different programming languages and compilers.

2 Configuring for your network

gator has been written to utilise multiple hosts on a network.  In
order to configure gator for your network, the gator.conf file needs
to contain information about all the hosts to be used.

Configuring gator.conf involves defining a set of variables and
assigning them values.  The syntax is the same as defining shell
variables in /bin/sh.

The following variable must be defined:

	num_hosts: the number of hosts available for benchmarking.  This
		may include the host from which gator is being run, if
		it is also being used to run the benchmarks.

For each host, the following variables need to be defined, where $i is
an integer between 1 and $num_hosts.

	host$i: the name of the host we are connecting to.  This is
		passed as a command-line argument to ssh(1).  Make sure
		you have a copy of the host's SSH public key in your
		cache before you run gator.

	workspace$i: the path to a directory containing gator.  Note
		that nothing is written to this directory, it is just
		used to access the dotime and evaluate.conf files from
		a remote host.  It can be the same on all hosts, as long
		as this directory is also mounted on all of the remote

	benchmarks$i: similar to workspace$i, except it contains the
		benchmarks directory from CVS.  Note that each host must
		have its own benchmarks directory.

	path$i: the path to the directory containing the compiler.  This
		is pre-pended to $PATH in the evaluate script.

The hosts in gator.conf are accessed using ssh(1) and ssh-agent(1).  It
is necessary to have SSH keys set up on each of these hosts.  See the
following URL for details on how to use ssh-agent(1):

As an example, suppose we are setting up gator to run on a network
containing two hosts named "jupiter" and "saturn".




In this example, $workspace1 and $workspace2 are both the same path, and
are on the same NFS-mounted filesystem.  All of the workspaces may be on
the same filesystem, although they don't have to be.  However, the
benchmark directories must be separate directories, so that separate
builds can be done on each host.  In this example, $benchmarks1 and
$benchmarks2 are located on their host's local filesystems.

3 Configuring for your software

The evaluate.conf file allows the user to change the benchmarking
information gathered by gator.  This is useful if gator is being
used to test different compilers, and/or different programs.

The syntax is identical to that of gator.conf (see section 2).

The following variable must be defined:

	num_progs: the number of programs used for benchmarking.  Note
		that if the number of programs is changed, the way that
		"fitness" is evaluated will need to be changed.  This
		should be done by defining a new set of "Weightings" in
		evolve.conf (see section 4).

For each program, the following variables need to be defined, where $i
is an integer between 1 and $num_progs.

	prog$i: the full path to the executable for the program (which
		may not yet be built).  This may or may not be contained
		under "$benchmarks" (see section 2).

	clean$i: the command used to completely clean up the source
		directory (e.g., "make realclean").

	compile$i: the command used to compile the program.  Note that
		you may assume there is a $flags shell variable which
		gives the optimization flags passed to the compiler.

	run$i: the command used to run the program.

For example, suppose we want to change the program being optimised.
The new program is in "benchmarks/progs/ray/proj.m", rather than
"mercury/samples/hello.m".  The first thing that needs to be done is
to copy the program's source code to any one of the hosts.  gator will
then find it and copy it to the other hosts.  Then, the gator.conf
file needs to be modified.  The new file is similar to the example
given above, except that the $benchmarks1 and $benchmarks2 directories
are different:


The evaluate.conf file would look like this:


	clean1="mmc --make proj.realclean; rm -rf Mercury"
	compile1="mmc --make -O0 $flags proj"
	run1="./proj -f 100 -S -s 0.4 2 -a 0.1 dh.scene 140 140 0 0 0 >dh.ppm"

The example above gives just one Mercury program.  The default
evolve.conf file is set up for just one Mercury program, so if more
programs or different compilers are used, it is necessary to modify
evolve.conf (see section 4 for details).

4 Configuring parameters for the genetic operators

If the intention is to, for example, optimise for space instead of time,
then it may be necessary to modify certain parameters of the genetic
operators.  This can be achieved by modifying the evolve.conf file,
which allows the user to tweak the parameters of certain genetic
operators including the fitness operator and the mutation operator.

The syntax of evolve.conf is a bit different to that of gator.conf and
evaluate.conf.  Currently, evolve.conf must contain two terms that can
be read by io.read/3.

The first term contains the "Weightings" used by phenotype.fitness/2.
This parameter is coupled with the number of programs being tested
(see section 3 on evaluate.conf).  For each program, there are three
measurements taken by the software: the compile time, the executable
size and the time taken to run the executable.  Because of this,
the list must be of length $num_progs * 3.

These next examples cause gator to search for a set of flags that
will minimize the compilation time for five programs,

			[ 1.0, 1.0, 1.0, 1.0, 1.0,
			  0.0, 0.0, 0.0, 0.0, 0.0,
			  0.0, 0.0, 0.0, 0.0, 0.0 ].

weight compile times and run times equally,

			[ 0.5, 0.5, 0.5, 0.5, 0.5,
			  0.0, 0.0, 0.0, 0.0, 0.0,
			  0.5, 0.5, 0.5, 0.5, 0.5 ].

or optimise for space, while ignoring the second program in the set.

			[ 0.0, 0.0, 0.0, 0.0, 0.0,
			  1.0, 0.0, 1.0, 1.0, 1.0,
			  0.0, 0.0, 0.0, 0.0, 0.0 ].

The second term contains a complete list of flags that can be passed to
the compiler.  This is used by genotype.mutation/5, which toggles a
random flag in an individual's genotype.

Suppose the evaluate.conf file (see section 3 for details) specifies two
programs, both of which are compiled with gcc(1).  In this case, the
first term would need to be a list of length $num_progs * 3 = 2 * 3 = 6.
The second term would need to contain a list of gcc optimisation
options, rather than mmc options.  The following example works for gcc

	[ 0.5, 0.5, 0.0, 0.0, 1.0, 1.0 ].

	[ "-fbranch-probabilities", "-fcaller-saves",
	  "-fcprop-registers", "-fcse-follow-jumps",
	  "-fcse-skip-blocks", "-fdata-sections", "-fdelayed-branch",
	  "-fdelete-null-pointer-checks", "-fexpensive-optimizations",
	  "-ffast-math", "-ffloat-store", "-fforce-addr", "-fforce-mem",
	  "-ffunction-sections", "-fgcse", "-fgcse-lm", "-fgcse-sm",
	  "-floop-optimize", "-fcrossjumping", "-fif-conversion",
	  "-fif-conversion2", "-finline-functions", "-fkeep-inline-functions",
	  "-fkeep-static-consts", "-fmerge-constants",
	  "-fmerge-all-constants", "-fmove-all-movables", "-fnew-ra",
	  "-fno-branch-count-reg", "-fno-default-inline", "-fno-defer-pop",
	  "-fno-function-cse", "-fno-guess-branch-probability", "-fno-inline",
	  "-fno-math-errno", "-fno-peephole", "-fno-peephole2",
	  "-funsafe-math-optimizations", "-ffinite-math-only",
	  "-fno-trapping-math", "-fno-zero-initialized-in-bss",
	  "-fomit-frame-pointer", "-foptimize-register-move",
	  "-foptimize-sibling-calls", "-fprefetch-loop-arrays",
	  "-freduce-all-givs", "-fregmove", "-frename-registers",
	  "-freorder-blocks", "-freorder-functions", "-frerun-cse-after-loop",
	  "-frerun-loop-opt", "-fschedule-insns", "-fschedule-insns2",
	  "-fno-sched-interblock", "-fno-sched-spec", "-fsched-spec-load",
	  "-fsched-spec-load-dangerous", "-fsignaling-nans",
	  "-fsingle-precision-constant", "-fssa", "-fssa-ccp", "-fssa-dce",
	  "-fstrength-reduce", "-fstrict-aliasing", "-ftracer",
	  "-fthread-jumps", "-funroll-all-loops", "-funroll-loops" ].

5 Further modifying the genetic operators

The genetic operators themselves can be modified directly.  They are
implemented in the following functions/predicates: