ppl/ppl-1.2/README.configure

Copyright (C) 2001-2010 Roberto Bagnara <bagnara@cs.unipr.it>
Copyright (C) 2010-2016 BUGSENG srl (http://bugseng.com)
See below for the copying conditions.


Configuration of the Parma Polyhedra Library
============================================

Contents
--------

 1. The Standard Thing (configure, make, make install)
 2. Using the Right Version of GMP
 3. Using the Right C and C++ Compilers
 4. Enabling the Use of Alternative Coefficient Types
 5. Configuring the Language Interfaces
 6. Configuring for Optimized Performance
 7. Advanced Performance Tuning
 8. Configuring for Debugging
 9. Programs that Come with the Library
10. Using the Git Sources


1. The Standard Thing (configure, make, make install)
-----------------------------------------------------

In an ideal situation (i.e., on a more or less standard Un*x
environment, with the right C++ compiler to compile the core library
as well as the right compilers to compile all the enabled language
interfaces, with the GMP library installed in a standard place and
provided the user is satisfied with all the options we chose as
defaults), a source distribution of the Parma Polyhedra Library (PPL)
can be unpacked, configured, built and installed with the following,
well-known procedure:

  $ tar jxf ppl-x.y.tar.bz2
  $ ./configure
  $ make
  $ su
  Password: <root password>
  $ make install

After successful completion of these steps the PPL is completely
installed on the system and can be used as expected.

On the other hand, the PPL `configure' shell script provides many
options to customize the build and installation process.  The
`INSTALL' file gives a detailed description of the non PPL-specific
aspects of the configuration, compilation and installation process and
describes the basic options of the `configure' script.  For a compact
summary of all the available configuration options, run the command

  $ ./configure --help

The PPL-specific aspects of the configuration, compilation and
installation process are discussed in the following sections.


2. Using the Right Version of GMP
---------------------------------

In order to use this version of the PPL you must make sure that:

(1) GMP version 4.1.3 or later is installed on your system;
(2) that this version was compiled with the C++ interface enabled;
(3) that this C++ interface was compiled with the same compiler
    version with which you will compile the PPL;
(4) that your C and C++ compilers and your linker will find _that_
    version of GMP and not others that may be present in your system.

Some binary distributions of GMP may contain a version that was compiled
with the C++ interface disabled, or compiled with a C++ compiler
implementing a different ABI than the compiler you will use to compile
the PPL.  In these (increasingly rare) cases the only reliable way to
ensure points (1), (2) and (3) above is to visit GMP's home page at

  http://gmplib.org/

and download the last available version.  Then decide where to install
it and call this place in your file system <GMP prefix>.  Then, unless
you have special needs, you can invoke the GMP's configure script with
the options

  --prefix=<GMP prefix> --enable-cxx

If the C++ compiler you will use to compile the PPL is not the default
on your system then, in order to satisfy point (3) above, you should
set the `CXX', `CXXFLAGS' and `CXXCPP' environment variables so as to
use the intended compiler with the intended options.  See the file
`INSTALL.autoconf' in the GMP distribution for more on this subject.

If you want to use the PPL ability to recover from out-of-memory
situations, you should use a version of GMP compiled with GCC (which
implies you should then compile also the PPL with GCC) using the
`-fexceptions' option.  To build such a version, you can use the
`CPPFLAGS' environment variable, so that it contains (among possibly
other compiler options) `-fexceptions'.  Again, see `INSTALL.autoconf'
in the GMP distribution for more on using environment variables to
influence the configure script.

In order to achieve point (4) above, if the directory <GMP prefix>
is not standard for your compiler and/or for your linker, you will
have to make sure the configure script of the PPL is invoked with,
among others, the option

  --with-gmp=<GMP prefix>

If you use shared libraries, consult the documentation of your dynamic
linker/loader (`man ld.so' will do on most Un*x-like systems) to see
how to make sure that GMP's shared library will be found at run-time
(setting the environment variable `LD_LIBRARY_PATH' to
"<GMP prefix>/lib:$LD_LIBRARY_PATH" or
"<GMP prefix>/lib64:$LD_LIBRARY_PATH" is the most commonly used
solution).

It is also possible to use a non-installed build of GMP.  In order to
do that you should configure the PPL with, among others, the option

  --with-gmp-build=<GMP build directory>


3. Using the Right C and C++ Compilers
--------------------------------------

The configure script of the PPL, as you can see by using its `--help'
option, besides recognizing `CC', `CXX', `CFLAGS', `CXXFLAGS' and
other environment variables, provides four switches with which you can
select the compilers and compilers' options to use for building the
library.  These switches are

  --with-cc=XXX           use XXX as the C compiler
  --with-cxx=XXX          use XXX as the C++ compiler
  --with-cflags=XXX       add XXX to the options for the C compiler
  --with-cxxflags=XXX     add XXX to the options for the C++ compiler

Among other things, the ability to specify the C and C++ compilation
flags allows you to use special compilation options ---such as
`-fno-threadsafe-statics'--- that, while not safe for general use,
may be adequate for your particular application.

Let us take the occasion to stress, once again, the fact that you
must use exactly the same C++ compiler to compile the C++ interface of GMP,
the PPL and your application, if it uses the C++ interface of the PPL.
It should be noted that no version of GCC prior to 4.0.3 is known to
reliably compile PPL 0.10.

Here is an example of a configuration that uses the Intel C/C++ compiler
version 11.1.x.  Assuming you have configured GMP with a command like

  CC=icc CXX=icpc /path/to/gmp-5.0.1/configure --enable-cxx \
    --prefix=/opt/intel/Compiler/11.1/072 \
    --libdir=/opt/intel/Compiler/11.1/072/lib/intel64

you can configure the PPL with a command like

  /path/to/ppl-x.y/configure --with-cxx=icpc --with-cc=icc \
    --with-cxxflags=-pch \
    --with-gmp=/opt/intel/Compiler/11.1/072

Notice that the `--with-cxxflags' option is not essential here and is
only included to show how extra compiler options can be passed to the
configure script.

As another example, here is how you can compile the PPL with
Comeau C/C++ 4.3.10.1.  First configure GMP with a command like

  CXX=como /path/to/gmp-5.0.1/configure --enable-cxx \
    --disable-shared --prefix=/opt/comeau/local

Then you can configure the PPL with a command like

  /path/to/ppl/configure --with-cc="como --c" --with-cxx="como -tused" \
    --with-cxxflags="-g++ --remarks --long_long \
    --display_error_number --diag_suppress 340,401,679" \
    --disable-shared --with-gmp=/opt/comeau/local

Notice the use of the option `--disable-shared' both in the configuration
of GMP and the configuration of the PPL.  This is due to the fact that
Comeau C/C++ 4.3.10.1 does not support shared libraries.


4. Enabling the Use of Alternative Coefficient Types
----------------------------------------------------

When speed is important and the numerical coefficients involved are
likely to be small, you can configure the PPL to use checked native
integers (8, 16, 32 or 64 bits wide) for the representation of the
coefficients.  This is a safe strategy since, when using checked
native integers, the library also performs systematic (yet efficient)
overflow detection and, in case of overflow, an exception is raised.
To enable the use of various kinds of coefficients, you can use
the configure option

  --enable-coefficients=TYPE

where TYPE is one of

  mpz,              use GMP unbounded integers (default);
  checked-int8,     use  8-bit checked integers;
  checked-int16,    use 16-bit checked integers;
  checked-int32,    use 32-bit checked integers;
  checked-int64,    use 64-bit checked integers.

When using checked integers it is also wise to increase the
optimization level, since their efficiency largely depends on the
compiler and on the optimization options used.  See below for how
to do that (in later releases we may try to make the choice of the
optimization options automatic).

If you want to test the overhead of checked integers with respect
to plain, unchecked native integers and you are really sure of what
you are doing, you may be interested to know that these additional
choices for TYPE are available:

  native-int8,     use  8-bit *unchecked* integers;
  native-int16,    use 16-bit *unchecked* integers;
  native-int32,    use 32-bit *unchecked* integers;
  native-int64,    use 64-bit *unchecked* integers.


5. Configuring the Language Interfaces
--------------------------------------

The PPL comes equipped with interfaces for several programming
languages.  Some of these interfaces are enabled by default,
meaning that, if the configuration script finds support for
a certain programming language, these interfaces are compiled
(with `make') and installed (with `make install').
The set of enabled interface can be customized with the configure option

  --enable-interfaces=INTERFACES

The INTERFACES argument can be

  none,            no language interface is enabled;
  all,             all language interfaces are enabled;

or any space-separated list of interface specifiers chosen among

  cxx,             the C++ interface;
  c,               the C interface;
  java,            the Java interface;
  ocaml,           the OCaml interface;
  ciao_prolog,     the Ciao Prolog interface;
  gnu_prolog,      the GNU Prolog interface;
  sicstus_prolog,  the SICStus Prolog interface;
  swi_prolog,      the SWI-Prolog interface;
  xsb_prolog,      the XSB interface;
  yap_prolog,      the YAP interface.

Note that, in order to build any interface different from the C++ one,
a recent enough version of GNU M4 is required (the configuration script
searches for one and gives an error if it cannot find it).

The instantiations for the domains for interfaces other than the main
C++ interface can be customized via the `instantiations' option for
the PPL `configure' shell script which is described below. Some
interfaces depend on language implementations that are somewhat
problematic, either because they tend to be installed in rather
unpredictable places, or because some published versions have bugs
that prevent the PPL interface to run correctly.  In these cases,
information is given in a README.* file.  Presently we have:

  README.java,
  README.ocaml,
  README.gprolog,
  README.swiprolog,
  README.yap.

For the Java interface, the `--with-java=DIR' configure option allows
to select the Java SDK root directory.  We have tested the Java interface
with the Java SE Development Kit 6 and OpenJDK 1.6.

For the OCaml interface, the `--with-mlgmp=DIR' configure option allows
to specify the installation directory of the ML GMP package (which allows
to use GMP numbers in OCaml programs).  By default, ML GMP is searched
in the `gmp' subdirectory of the OCaml standard library directory.

The C++ interface provides access to all the numerical abstractions
provided by the PPL.  The majority of these (we are talking about
hundreds of different numerical abstractions) are provided by means
of C++ templates.  The other languages interfaced to the PPL, except
Java, do not have this facility.  Moreover, at the time of writing
we do not know if and to which extent C++ templates can be mapped
onto Java generics.  As a result, for all the language interfaces
but the C++ one, the instantiation of the template-based numerical
abstractions must be done at library-compile-time (instead of
application-compile-time).  A small set of instantiations is enabled
by default.  Currently this set is given by

  Polyhedron (which stands for both C_Polyhedron and NNC_Polyhedron),
  Grid,
  Rational_Box,
  BD_Shape<mpz_class>,
  BD_Shape<mpq_class>,
  Octagonal_Shape<mpz_class>,
  Octagonal_Shape<mpq_class>,
  Constraints_Product<C_Polyhedron, Grid>,
  Pointset_Powerset<C_Polyhedron>,
  Pointset_Powerset<NNC_Polyhedron>,

plus, if the host architecture supports double precision floating point
numbers conforming to the IEEE 754 standard,

  Double_Box,
  BD_Shape<double>,
  Octagonal_Shape<double>.

To enable a different set of instantiations, the configure option

  --enable-instantiations=INSTANTIATIONS

The list of of possibilities for the `INSTANTIATIONS' argument can be
obtained by omitting the argument, i.e., with the configure option

  --enable-instantiations

Note that the stand-alone `Polyhedron' instantiation must be specified
without any topology `C_' or `NNC_' as they are added automatically
and both the domains `C_Polyhedron' and `NNC_Polyhedron' will be
generated.


6. Configuring for Optimized Performance
----------------------------------------

By default, the PPL is compiled with all the optimizations provided
by the compiler that do not involve a space-speed tradeoff (a.k.a.
-O2 optimization).  The same optimization level can be obtained by
using the configure options

  --enable-optimization
or
  --enable-optimization=standard

You can try to squeeze more speed from your compiler by using the
`--enable-optimization=speed' compiler option (a.k.a. -O3
optimization): this is recommended if you use the checked integers
coefficients, even though it does not come with an 100% guarantee of
extra performance.  With the `--enable-optimization=sspeed'
optimization even more optimization is requested, possibly at the cost
of making debugging impossible on some machines.  The
`--enable-optimization=size' configure option instructs the compiler
to optimize for size and for speed, but only for speed improvements do
not increase code size.

Further optimization can be requested at the expense of portability
of the generated code.  This can be achieved by means of the configure option

  --enable-arch[=ARCH]

If the ARCH argument is omitted the configure script attempts to
detect the architecture of the system.  Allowed values for ARCH can be
found in the documentation of the `-march' option of the used C/C++
compiler.

For floating point computations, the option

  --enable-fpmath=INSTRUCTION_SET

allows for selecting, on the IA32 and x86_64, the floating point instruction
set.  The allowed values for INSTRUCTION_SET are `sse', `sse2', `387,
`sse+387', and `sse2+387', `default', and `no'.  The latter option, which
is equivalent to specifying `--disable-fpmath', has the effect of disabling
all floating point computation and, consequently, all the numerical
abstractions based on floating point numbers.

On the other hand, there are configure options to request lesser
degrees of optimization for the sake of debugging.  These are,
in decreasing order of optimization, `--enable-optimization=mild'
(a.k.a. -O1 optimization), `--enable-optimization=no' or, equivalently
`--disable-optimization', and `--enable-optimization=zero'
(a.k.a. -O0 optimization).  See below for more information on the
configure options that are useful for debugging purposes.


7. Advanced Performance Tuning
------------------------------

Starting from version 1.0, the library fully supports two different
representations for rows (i.e., sequences of coefficients):

  - the "dense" representation is an array-like representation tailored
    to sequences having most of their coefficients different from zero;

  - the "sparse" representation saves memory space (as well as CPU
    cycles) when most of the coefficients in the sequence are zero.

A generic interface allows for a seamless interaction between the
dense and the sparse row representation. Most library entities (linear
expressions, constraints, generators, congruences, and their systems)
can be built using either representation, specified as a constructor's
argument. Reasonable default values for the row representation are
provided for each library entity, automatically leading to significant
memory space savings even in old client/library code, e.g., when
dealing with constraint systems describing weakly relational
abstractions such as boxes and octagonal shapes.

If desired, these default values can be customized to user's needs by
changing just a few lines of library code. For instance, the
constraint systems stored inside C_Polyhedron and NNC_Polyhedron
objects can be made to use the sparse representation by just changing
the following line in Polyhedron_defs.hh:

  static const Representation default_con_sys_repr = DENSE;

to become

  static const Representation default_con_sys_repr = SPARSE;


8. Configuring for Debugging
----------------------------

By default, the PPL is configured with debugging information enabled.
In case you are absolutely, definitely, positively sure that you will
not need to engage in debugging sessions and wish to save some little
disk space and compilation time/memory you can configure with the
`--disable-debugging' option.

When the results you obtain with the PPL surprise you and make you think
there might be a bug somewhere, it is a good idea to build a version
of the library using the `--enable-assertions' configure option.  This
causes many run-time assertions to be checked and often result in the
easier identification of bugs in your application or the library itself.
Even more run-time assertions can be enabled with the
`--enable-more-assertions': this causes some PPL objects to carry
additional data fields for the purpose of making extra checks possible.
Of course, this breaks the ABI of the library, so you should recompile
the part of your application that depends on the PPL.

If you are disappointed by performance of the library and would like
to check where the computation time is being spent, you can use the
`--enable-profiling' option to generate a version that writes profile
information suitable for the `gprof' analysis program.

The `--enable-valgrind-tests' causes most of the tests run by `make check'
under Valgrind's Memcheck tool.  This will show you if the library has
memory leaks.  At release time, we guarantee that Memcheck does not
reveal any memory leak for tests using the C++ and the C interfaces.
We are not able to make a similar guarantee for other interfaces because
the corresponding language implementations (e.g., OCaml and SWI-Prolog)
purposely do not deallocate all memory on exit.

In order to assess the coverage of the PPL test suite, the
`--enable-coverage' configure option is provided.  This causes instrumented
code to be used in conjunction with the `gcov' coverage testing tool.


9. Programs that Come with the Library
--------------------------------------

The PPL is shipped with two programs that are interesting per se, and
allow to sanity-check the build as well as to obtain performance
comparisons.  The first such program is `ppl_lpsol', which offers some
of the functionality of GLPK's `glpsol' using the service of the
PPL, including its simplex solver.  Since `ppl_lpsol' uses GLPK's
input routines, it is only built if a suitable version of GLPK is
available.  If you prefer `ppl_lpsol' not to be built, use the
configure option

  --disable-ppl_lpsol

Another program that is built by default and is used for regression
testing and build validation is `ppl_lcdd'.  This is a program for
vertex/facet enumeration, accepting the same input format as the
similar programs shipped with cddlib and lrslib.  If you prefer `ppl_lcdd'
not to be built, use the configure option

  --disable-ppl_lcdd

Disabling these programs will shorten the compilation time by a few
seconds, and the time spent in `make check' by a dozen of minutes.
In exchange, you will give up an important opportunity to discover
whether the version of PPL you have built has been miscompiled.


10. Using the Git Sources
-------------------------

If you use the Git sources, then you need recent versions of Autoconf
Automake and Libtool installed.  After a `git clone' or `git pull'
you should run the `autoreconf' command.  In case you have fiddled
around with some of the configuration files, or if you have problems
you cannot explain otherwise, use `autoreconf -f'.


--------

Copyright (C) 2001-2010 Roberto Bagnara <bagnara@cs.unipr.it>
Copyright (C) 2010-2016 BUGSENG srl (http://bugseng.com)

This document describes the Parma Polyhedra Library (PPL).

Permission is granted to copy, distribute and/or modify this document
under the terms of the GNU Free Documentation License, Version 1.2
or any later version published by the Free Software Foundation;
with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
The license is included, in various formats, in the `doc' subdirectory
of each distribution of the PPL in files named `fdl.*'.

The PPL is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation; either version 3 of the License, or (at your
option) any later version.  The license is included, in various
formats, in the `doc' subdirectory of each distribution of the PPL in
files named `gpl.*'.

The PPL is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
for more details.

If you have not received a copy of one or both the above mentioned
licenses along with the PPL, write to the Free Software Foundation,
Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02111-1307, USA.

For the most up-to-date information see the Parma Polyhedra Library
site: http://bugseng.com/products/ppl/ .