How to install gnu parallel on mac
The purpose of this post has been to essentially highlight all the changes I had to make in order to successfully run the toy example from the book on a mixture of OS X and Linux machines all running locally. (Again, notice the additional ‘-‘ in the paste commands). This command is also from the book and will give you the sum – you basically just summed 100 numbers each separately on the slave machines through different parallel processes, and then summed the 10 sums locally. $ seq 1000 | parallel -N100 –pipe –slf instances “paste -sd+ – | bc” | paste -sd+ – | bc Cadmius happens to have 8 CPUs (and 32 cores).įinally, run the following to sum the numbers in parallel and then sum the 10 sums on the host machine:
HOW TO INSTALL GNU PARALLEL ON MAC INSTALL
In this case I did install Parallel on the master and two slaves, but it seems Parallel doesn’t like the fact that macusers-Macbook is an older machine with a Core 2 Duo? Not sure about that. I’ve mentioned how Parallel doesn’t need to be installed on all machines for basic usage. The output shows the hostnames and the number of numbers passed over to the slaves. With it, both OS X and Ubuntu seem happy (yet you can see the differences in the outputs from the two kinds of machines).Īpart from that difference, the command is copied from the book it is basically generating a sequence of 1000 numbers, and distributing them to the slaves. The book doesn’t have it because you do not need it on Linux. Notice the additional ‘-‘ after the arguments to paste. The main machine through which I am parallelizing things is also running OS X Mavericks. In my case, Cadmius happens to be Ubuntu 14.04, and macusers-Macbook is running OS X Mavericks. Next, create your instances file (named ‘instances’), and add the hostnames of your local machines as shown in the screenshot. First, you can install GNU Parallel on OS X through Homebrew: (sudo) brew install parallel Next, create your instances file (named ‘instances’), and add the hostnames of your local machines as shown in the screenshot. Here is a walkthrough that basically replicates the toy example in the book, but highlights the differences you’ll need to incorporate in an OS X environment.įirst, you can install GNU Parallel on OS X through Homebrew: (3) you are using the OS X variant of paste (which has a nuance compared to the Ubuntu version) (2) all your machines are local (as in connected through a LAN) (1) you are primarily using OS X and might have some Ubuntu machines as some of your instances I am presenting a tutorial that works with the premise that (3) you are using GNU paste that comes pre-installed on all Ubuntu systems (2) you are using a bunch of Amazon EC2 instances to do your parallelization (and hence need to find out the IPs of all your instances in a non-straightforward way) (1) all machines you are using are running Ubuntu or some variant of Linux The toy example/ tutorial in the book makes three assumptions:
HOW TO INSTALL GNU PARALLEL ON MAC HOW TO
The book Data Science at the Command Line discusses, amongst several other things, how to use GNU Parallel to distribute your data over different machines. GNU parallel can often be used as a substitute for xargs or cat | bash.GNU Parallel is a great utility to parallelize any computation through the command line. If no command is given, the line of input is executed. This makes it possible to use output from GNU parallel as input for other programs.įor each line of input GNU parallel will execute command with the line as arguments. GNU parallel makes sure output from the commands is the same output as you would get had you run the commands sequentially. If you use ppss or pexec you will find GNU parallel will often make the command easier to read. If you write loops in shell, you will find GNU parallel may be able to replace most of the loops and make them run faster by running several jobs in parallel. If you use xargs today you will find GNU parallel very easy to use as GNU parallel is written to have the same options as xargs. The typical input is a list of files, a list of hosts, a list of users, a list of URLs, or a list of tables. A job is typically a single command or a small script that has to be run for each of the lines in the input.
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GNU Parallel version 20100620 is a shell tool for executing jobs in parallel locally or using remote machines.