KyleThis 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.RegardsI 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 ( http://mesos.apache.org/ ). You can see an overview of the Mesos architecture at https://github.com/apache/mesos/blob/master/docs/Mesos-Architecture.mdThe 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 as:- Hadoop (https://github.com/mesos/hadoop)- Spark (http://spark-project.org)And you can find example Python framework at https://github.com/apache/mesos/tree/master/src/examples/pythonIntegration 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.Kyle___________________________________________________________
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MCS, Argonne National Laboratory
Computation Institute, University of Chicago