Swift indeed is a complete framework for distributed computing.
Distributing files out to cluster nodes, starting processes, bringing back
result files to submit host is done out of the box (stagein-exec-stageout
We can discuss offline if you are interested in giving it a shot.
On Mon, Oct 28, 2013 at 4:14 PM, Kyle Ellrott <kellrott(a)soe.ucsc.edu> wrote:
You probably are a good person to get an opinion from. My plan
write new frameworks, but rather use existing libraries that can
communicate with Mesos to setup their parallel environments.
But for Swift, you would probably want to write a new framework. Just
looking at Swift, I imagine one of the harder parts is just getting the
system setup on a cluster (ie distributing out files to remote nodes,
making sure that you have a way to start processes on those nodes and have
them know where to find the master), it seems like Swift could benefit from
having a Mesos based framework. Do you think it would enable you to have a
'zero-config' startup of a distributed Swift application?
On Mon, Oct 28, 2013 at 1:51 PM, Ketan Maheshwari <
> Hi Kyle,
> We have a similar ongoing development wherein we are working on
> integrating our Swift framework ( swift-lang.org
) with Galaxy. The goal
> is to enable Galaxy based applications to run on a variety of distributed
> resources via various integration schemes as suitable to application and
> underlying execution environment.
> Here is an abstract of a paper (co-authored with Ravi, who responded on
> this thread) we will be presenting in a workshop at the upcoming SC 13
> "The Galaxy platform is a web-based science portal for scientific
> computing supporting Life Sciences users community. While user-friendly and
> intuitive for doing small to medium scale computations, it currently has a
> limited support for large-scale, parallel and distributed computing. The
> Swift parallel scripting framework is capable of composing ordinary
> applications into parallel scripts that can be run on multi-scale
> distributed and performance computing platforms. In complex distributed
> environments, often the user end of application lifecycle slows down
> because of the technical complexities brought in by the scale, access
> methods and resource management nuances. Galaxy offers a simple way of
> designing, composing, executing, reusing, and reproducing application runs.
> An integration between Swift and Galaxy systems can accelerate science as
> well as bring the respective user communities together in an interactive,
> user-friendly, parallel and distributed data analysis environment enabled
> on a broad range of computational infrastructures."
> Kindly let us know if you need a hands on for the various tools we have
> already developed.
> On Mon, Oct 28, 2013 at 3:07 PM, Kyle Ellrott <kellrott(a)soe.ucsc.edu>wrote:
>> I don't think implementation will be very difficult. The bigger question
>> is this a technology people are open to?
>> The nearest competitor is YARN (
>> Mesos seems a bit more geared toward general purpose usage (with several
>> existing frameworks), while YARN seems more specific to Hadoop. But I'd be
>> glad to hear some other thoughts.
>> On Mon, Oct 28, 2013 at 12:55 PM, Ravi K Madduri
>>> This is something I am very interested in. The three parts below make
>>> sense to me. I would be very happy to discuss further and provide any help
>>> to move this forward.
>>> On Oct 26, 2013, at 2:43 PM, Kyle Ellrott <kellrott(a)soe.ucsc.edu>
>>> I think one of the aspects where Galaxy is a bit soft is the ability to
>>> do distributed tasks. The current system of split/replicate/merge tasks
>>> based on file type is a bit limited and hard for tool developers to expand
>>> upon. Distributed computing is a non-trival thing to implement and I think
>>> it would be a better use of our time to use an already existing framework.
>>> And it would also mean one less API for tool writers to have to develop for.
>>> I was wondering if anybody has looked at Mesos (
). You can see an overview of the Mesos
>>> architecture at
>>> The important thing about Mesos is that it provides an API for C/C++,
>>> Java/Scala and Python to write distributed frameworks. There are already
>>> implementations of frameworks for common parallel programming systems such
>>> - Hadoop (https://github.com/mesos/hadoop
>>> - MPI (
>>> - Spark (http://spark-project.org
>>> And you can find example Python framework at
>>> Integration with Galaxy would have three parts:
>>> 1) Add a system config variable to Galaxy called 'MESOS_URL' that is
>>> then passed to tool wrappers and allows them to contact the local mesos
>>> infrastructure (assuming the system has been configured) or pass a null if
>>> the system isn't available.
>>> 2) Write a tool runner that works as a mesos framework to executes
>>> single cpu jobs on the distributed system.
>>> 3) For instances where mesos is not available at a system wide level
>>> (say they only have access to an SGE based cluster), but the user wants to
>>> run distributed jobs, write a wrapper that can create a mesos cluster using
>>> the existing queueing system. For example, right now I run a Mesos system
>>> under the SGE queue system.
>>> I'm curious to see what other people think.
>>> Please keep all replies on the list by using "reply all"
>>> in your mail client. To manage your subscriptions to this
>>> and other Galaxy lists, please use the interface at:
>>> To search Galaxy mailing lists use the unified search at:
>>> Ravi K Madduri
>>> MCS, Argonne National Laboratory
>>> Computation Institute, University of Chicago
>> Please keep all replies on the list by using "reply all"
>> in your mail client. To manage your subscriptions to this
>> and other Galaxy lists, please use the interface at:
>> To search Galaxy mailing lists use the unified search at: