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](https://github.com/JuliaLang/julia/blob/master/LICENSE.md), the distribution created by the techniques described herein will be GPL licensed, as various dependent libraries such as `FFTW`, `Rmath`, `SuiteSparse`, and `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 pregenerate the `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 make full-source-dist 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" Target Architectures -------------------- 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 `make`, 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 `x86-64` and `core2` (for 64-bit builds) and `pentium4` (for 32-bit builds). Unfortunately, CPUs older than Pentium 4 are currently not supported (see [this issue](https://github.com/JuliaLang/julia/issues/7185)). The full list of CPU targets supported by LLVM can be obtained by running `llc -mattr=help`. Linux ----- On Linux, `make binary-dist` creates a tarball that contains a fully functional Julia installation. If you wish to create a distribution package such as a `.deb`, or `.rpm`, some extra effort is needed. See the [julia-debian](https://github.com/staticfloat/julia-debian) repository for an example of what metadata is needed for creating `.deb` packages for Debian and Ubuntu-based systems. See the [Fedora package](https://admin.fedoraproject.org/pkgdb/package/julia/) for RPM-based distributions. Although we have not yet experimented with it, [Alien](https://wiki.debian.org/Alien) could be used to generate Julia packages for various Linux distributions. Julia supports overriding standard installation directories via `prefix` and other environment variables you can pass when calling `make` and `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 `$prefix/etc/julia/juliarc.jl` as an installation-wide initialization file. This file can be used by distribution managers to provide paths to various binaries such as a bundled `git` executable (as we do on OS X), or to setup paths (as we do on Windows). For Linux distribution packages, if `$prefix` is set to `/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 pass `sysconfdir=/etc` to `make` when building and Julia will first check `/etc/julia/juliarc.jl` before trying `$prefix/etc/julia/juliarc.jl`. OS X ---- 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 with `make` when building Julia proper. This will then create a `.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](http://julialang.org/downloads/) for OS X 10.6 and 10.7+. Windows ------- 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 available](https://github.com/JuliaLang/julia/blob/master/README.windows.md). However the important steps for redistribution are to ensure to `make win-extras` in between `make` and `make binary-dist`. After that process is completed, the `.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 `make` option called `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, but `libopenblas.so` is not. We recommend using the former for optimal performance. To choose an OpenBLAS library whose name is different from the default `libopenblas.so`, pass `LIBBLAS=-l$(YOURBLAS)` and `LIBBLASNAME=lib$(YOURBLAS)` to `make`, replacing `$(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 `.so` symlink. Finally, OpenBLAS includes its own optimized version of LAPACK. If you set `USE_SYSTEM_BLAS=1` and `USE_SYSTEM_LAPACK=1`, you should also set `LIBLAPACK=-l$(YOURBLAS)` and `LIBLAPACKNAME=lib$(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. Compilation scripts =================== The [julia-nightly-packaging](https://github.com/staticfloat/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](https://travis-ci.org/JuliaLang/julia/builds) tests.