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Setting up gcc / OpenMP on OSX (Homebrew edition)
While XCode tools still has a command-line C compiler, In recent versions of OS X (I think 10.7 and later) have switched to clang/llvm (mostly because Apple wants all the benefits of Open Source without having to contribute back and clang is BSD licensed). Secondly, I think all you have to do to install XCode is to download it from the App store. Traditionally, gcc and g are both components of the GNU C compiler suite. Gcc is the C compiler, and g is the C compiler. On current versions of Mac OS X, the commands gcc and g are both treated as alternate names for clang and clang, which are components of the Clang C compiler. However, this compiler is almost entirely compatible.
Note: This is part of a series of “how-to” blog posts to help new users and developers of BioFVM and PhysiCell. This guide is for OSX users. Windows users should use this guide instead. A Linux guide is expected soon.
These instructions should get you up and running with a minimal environment for compiling 64-bit C++ projects with OpenMP (e.g., BioFVM and PhysiCell) using gcc. These instructions were tested with OSX 10.11 (El Capitan) and 10.12 (Sierra), but they should work on any reasonably recent version of OSX.
In the end result, you’ll have a compiler and key makefile capabilities. The entire toolchain is free and open source.
- Click on Settings, pull down to Compiler Settings, and pull down to Workspace. Change the language to C. Select 'c (g) - Mac OS X' or 'g - generic', click on Use, and click on OK. You are now ready to start developing in C/C and you have two ways to proceed, depending on your personal preferences.
- The GNU Compiler Collection or GCC for short, comprises front ends for C, Objective-C, C, Java, Fortran, Go and Ada, along with libraries for the mentioned languages. GCC us the main component of the GNU toolchain, it is distributed under the GNU General Public License.
Of course, you can use other compilers and more sophisticated integrated desktop environments, but these instructions will get you a good baseline system with support for 64-bit binaries and OpenMP parallelization.
Note 1:OSX / Xcode appears to have gcc out of the box (you can type “gcc” in a Terminal window), but this really just maps back onto Apple’s build of clang. Alas, this will not support OpenMP for parallelization.
Note 2: In this post, we showed how to set up gcc using the popular MacPorts package manager. Because MacPorts builds gcc (and all its dependencies!) from source, it takes a very, very long time. On my 2012 Macbook Air, this step took 16 hours. This tutorial uses Homebrew to dramatically speed up the process!
Note 3: This is an update over the previous version. It incorporates new information that Xcode command line tools can be installed without the full 4.41 GB download / installation of Xcode. Many thanks to Walter de Back and Tim at the Homebrew project for their help!
What you’ll need:
- XCode Command Line Tools: These command line tools are needed for Homebrew and related package managers. Installation instructions are now very simple and included below. As of January 18, 2016, this will install Version 2343.
- Homebrew: This is a package manager for OSX, which will let you easily download and install many linux utilities without building them from source. You’ll particularly need it for getting gcc. Installation is a simple command-line script, as detailed below. As of August 2, 2017, this will download Version 1.3.0.
- gcc (from Homebrew): This will be an up-to-date 64-bit version of gcc, with support for OpenMP. As of August 2, 2017, this will download Version 7.1.0.
Main steps:
1) Install the XCode Command Line Tools
Open a terminal window (Open Launchpad, then “Other”, then “Terminal”), and run:
A window should pop up asking you to either get Xcode or install. Choose the “install” option to avoid the huge 4+ GB Xcode download. It should only take a few minutes to complete.
2) Install Homebrew
Open a terminal window (Open Launchpad, then “Other”, then “Terminal”), and run:
Dragon ball xenoverse for mac download. Let the script run, and answer “y” whenever asked. This will not take very long.
3) Get, install, and prepare gcc
Open a terminal window (see above), and search for gcc, version 7.x or above
You should see a list of packages, including gcc7. (In 2015, this looked like “gcc5”. In 2017, this looks like “gcc@7”.)
Then, download and install gcc:
Then, download and install gcc:
This will download whatever dependencies are needed, generally already pre-compiled. The whole process should only take five or ten minutes.
Lastly, you need to get the exact name of your compiler. In your terminal window, type g++, and then hit tab twice to see a list. On my system, I see this:
Look for the version of g++ without an “mp” (from MacPorts) in its name. In my case, it’s g++-7. Double-check that you have the right one by checking its version. It should look something like this:
Notice that Homebrew shows up in the information. The correct compiler is g++-7.
PhysiCell Version 1.2.2 and greater use a system variable to record your compiler version, so that you don’t need to modify the CC line in PhysiCell Makefiles. Set the PHYSICELL_CPP variable to record the compiler you just found above. For example, on the bash shell:
One last thing: If you don’t update your paths, make will may fail as it continues to combine Apple’s “gcc” toolchain with real gcc. (This seems to happen most often if you installed an older gcc like gcc5 with MacPorts earlier.) You may see errors like this:
Mac Os X User Interface
To avoid this, run:
Note that you’ll need to open a new Terminal window for this fix to apply.
4) Test your setup
I wrote a sample C++ program that tests OpenMP parallelization (32 threads). If you can compile and run it, it means that everything (including make) is working! :-)
Make a new directory, and enter it
Open Terminal (see above). You should be in your user profile’s root directory. Itunes 7.7 1 download mac. Make a new subdirectory called GCC_test, and enter it.
Grab a sample parallelized program:
Download a Makefile and C++ source file, and save them to the GCC_test directory. https://treeproxy505.weebly.com/blog/cant-pause-a-mac-download-wtf. Here are the links:
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- Makefile: [click here]
- C++ source: [click here]
Note: The Makefiles in PhysiCell (versions > 1.2.1) can use an environment variable to specify an OpenMP-capable g++ compiler. If you have not yet done so, you should go ahead and set that now, e.g., for the bash shell:
Compile and run the test:
Go back to your (still open) command prompt. Compile and run the program:
The output should look something like this:
Note 1: If the make command gives errors like “**** missing separator”, then you need to replace the white space (e.g., one or more spaces) at the start of the “$(COMPILE_COMMAND)” and “rm -f” lines with a single tab character.
Note 2: If the compiler gives an error like “fatal error: ‘omp.h’ not found”, you probably used Apple’s build of clang, which does not include OpenMP support. You’ll need to make sure that you set the environment variable PHYSICELL_CPP as above (for PhysiCell 1.2.2 or later), or specify your compiler on the CC line of your makefile (for PhysiCell 1.2.1 or earlier).
Now, let’s verify that the code is using OpenMP.
Open another Terminal window. While the code is running, run top. Take a look at the performance, particularly CPU usage. While your program is running, you should see CPU usage fairly close to ‘100% user’. (This is a good indication that your code is running the OpenMP parallelization as expected.)
What’s next?
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Download a copy of PhysiCell and try out the included examples! Visit BioFVM at MathCancer.org.
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- PhysiCell links:
- PhysiCell Method Paper at bioRxiv: https://doi.org/10.1101/088773
- PhysiCell on MathCancer: http://PhysiCell.MathCancer.org
- PhysiCell on SourceForge: http://PhysiCell.sf.net
- PhysiCell on github: http://github.com/MathCancer/PhysiCell
- PhysiCell tutorials: [click here]
- BioFVM links:
- BioFVM announcement on this blog: [click here]
- BioFVM on MathCancer.org: http://BioFVM.MathCancer.org
- BioFVM on SourceForge: http://BioFVM.sf.net
- BioFVM Method Paper in BioInformatics: http://dx.doi.org/10.1093/bioinformatics/btv730
- BioFVM tutorials: [click here]
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