Notes for building binary distributions
These notes are for those wishing to compile a binary distribution of Julia for distribution on various platforms. We love users spreading Julia as far and wide as they can, trying it out on as wide an array of operating systems and hardware configurations as possible. As each platform has specific gotchas and processes that must be followed in order to create a portable, working Julia distribution, we have separated most of the notes by OS.
Note that while the code for Julia is
MIT-licensed, with a few exceptions,
the distribution created by the techniques described herein will be
GPL licensed, as various dependent libraries such as
git are GPL licensed. We do hope to have a
non-GPL distribution of Julia in the future.
Versioning and Git
The Makefile uses both the
VERSION file and commit hashes and tags from the
git repository to generate the
base/version_git.jl with information we use to
fill the splash screen and the
versioninfo() output. If you for some reason
don't want to have the git repository available when building you should
base/version_git.jl file with:
make -C base version_git.jl.phony
Julia has lots of build dependencies where we use patched versions that has not yet been included by the popular package managers. These dependencies will usually be automatically downloaded when you build, but if you want to be able to build Julia on a computer without internet access you should create a full-source-dist archive with the special make target
that creates a julia-version-commit.tar.gz archive with all required dependencies.
When compiling a tagged release in the git repository, we don't display the branch/commit hash info in the splash screen. You can use this line to show a release description of up to 45 characters. To set this line you have to create a Make.user file containing:
override TAGGED_RELEASE_BANNER = "my-package-repository build"
By default, Julia optimizes its system image to the native architecture of the build machine. This is usually not what you want when building packages, as it will make Julia fail at startup on any machine with incompatible CPUs (in particular older ones with more restricted instruction sets).
We therefore recommend that you pass the
MARCH variable when calling
setting it to the baseline target you intend to support. This will determine
the target CPU for both the Julia executable and libraries, and the system
image (the latter can also be set using
JULIA_CPU_TARGET). Typically useful
values for x86 CPUs are
core2 (for 64-bit builds) and
pentium4 (for 32-bit builds). Unfortunately, CPUs older than Pentium 4
are currently not supported (see
The full list of CPU targets supported by LLVM can be obtained by running
make binary-dist creates a tarball that contains a fully
functional Julia installation. If you wish to create a distribution
package such as a
.rpm, some extra effort is needed. See the
for an example of what metadata is needed for creating
for Debian and Ubuntu-based systems. See the
for RPM-based distributions. Although we have not yet experimented
with it, Alien could be used to
generate Julia packages for various Linux distributions.
Julia supports overriding standard installation directories via
and other environment variables you can pass when calling
make install. See Make.inc for their list.
DESTDIR can also be used
to force the installation into a temporary directory.
By default, Julia loads
$prefix/etc/julia/juliarc.jl as an
installation-wide initialization file. This file can be used by
distribution managers to provide paths to various binaries such as a
git executable (as we do on OS X), or to setup paths (as
we do on Windows). For Linux distribution packages, if
/usr, there is no
/usr/etc to look into. This requires
the path to Julia's private
etc directory to be changed. This can
be done via the
sysconfdir make variable when building. Simply
make when building and Julia will first
/etc/julia/juliarc.jl before trying
To create a binary distribution on OSX, build Julia first, then cd to
contrib/mac/app, and run
make with the same makevars that were used
make when building Julia proper. This will then
.dmg file in the
contrib/mac/app directory holding a
completely self-contained Julia.app.
Note that if you want your
.app to be able to run on OSX 10.6 Snow
Leopard, you must pass
USE_SYSTEM_LIBUNWIND=1 as one of the make
variables passed to both
make processes. This disables the use of
libosxunwind, a more modern libunwind that relies on OS features
available only in 10.7+. This is the reason why we offer separate
downloads for OS X 10.6 and 10.7+.
The best supported method of creating a Julia distribution on Windows
is to cross-compile from a Linux distribution such as Ubuntu. In-depth
compilation instructions are
However the important steps for redistribution are to ensure to
win-extras in between
make binary-dist. After that process is
.zip file created in the head Julia directory will
hold a completely self-contained Julia.
Notes on BLAS and LAPACK
Julia builds OpenBLAS by default, which includes the BLAS and LAPACK libraries. On 32-bit architectures, Julia builds OpenBLAS to use 32-bit integers, while on 64-bit architectures, Julia builds OpenBLAS to use 64-bit integers (ILP64). It is essential that all Julia functions that call BLAS and LAPACK API routines use integers of the correct width.
Most BLAS and LAPACK distributions provided on linux distributions, and even commercial implementations ship libraries that use 32-bit APIs. In many cases, a 64-bit API is provided as a separate library.
When using vendor provided or OS provided libraries, a
USE_BLAS64 is available as part of the Julia build. When doing
make USE_BLAS64=0, Julia will call BLAS and LAPACK assuming a 32-bit
API, where all integers are 32-bit wide, even on a 64-bit architecture.
Other libraries that Julia uses, such as ARPACK and SuiteSparse also use BLAS and LAPACK internally. The APIs need to be consistent across all libraries that depend on BLAS and LAPACK. The Julia build process will build all these libraries correctly, but when overriding defaults and using system provided libraries, this consistency must be ensured.
Also note that Linux distributions sometimes ship several versions of
OpenBLAS, some of which enable multithreading, and others only working
in a serial fashion. For example, in Fedora,
libopenblasp.so is threaded,
libopenblas.so is not. We recommend using the former for optimal
performance. To choose an OpenBLAS library whose name is different from
$(YOURBLAS) with the
name of your library. You can also add
.so.0 to the name of the library
if you want your package to work without requiring the unversioned
Finally, OpenBLAS includes its own optimized version of LAPACK. If you
USE_SYSTEM_LAPACK=1, you should also set
LIBLAPACKNAME=lib$(YOURBLAS). Else, the
reference LAPACK will be used and performance will typically be much lower.
Notes on Rmath
Rmath is a library from R, which includes basic statistical functions. Julia uses a patched version of Rmath, which uses DSFMT as its underlying generator, and faster normal random number generators. If the stock Rmath provided by various linux distributions is used, the underlying random streams will not be the same for different RNGs in Base and Distributions.jl.
It is highly recommended that the patched Rmath provided by Julia is used.
The julia-nightly-packaging repository contains multiple example scripts to ease the creation of binary packages. It also includes miscellaneous tools to do things such as fetching the last good commit that passed the Travis tests.