> Very interesting approach, thanks for reaching out and open sourcing your > stuff!
thanks for your time having a look at this, and your comments and advice ! > > What form would this contribution take? Are there changes that need to be > made to the Galaxy core that need to be made or were you hoping to mark > up the core tools with tardis markup? I would be happy to help adjust > (generalize?) the framework to support your use cases if there are things to > be done in that arena, but I would be skeptical about marking up the core > tools with tardis descriptions and introducing a dependency between these > tools an tardis. yes I agree. I guess I am using this Galaxy-embedding hack (...i.e. modifying tool configs so that they can splice in tardis-related markup of the command string) because it’s a way I can try out galaxy-embedding of this approach , in an exploratory way (but also getting some good data processing throughput gains along the way of course !). I should have thought about and made that qualification. > > I would imagine most Galaxy developers would agree with me that the > Galaxy philosophy is that the tool should be agnostic to the job > manager/DRM used - in fact they should all ideally work with the local job > runner with no DRM available at all. Handling that interaction is the > responsibility of job runners. Galaxy is structured in layers too, it just job > manager interaction is above the tool layer not below it. > I am not certain this is the correct philosophy - but I suspect it is the > Galaxy > philosophy and it is how Galaxy main the devteam tools are likely to continue > to operate. thanks - that’s a good point about the ordering of the layers. what I was thinking of exploring next, was the possibility of the galaxy engine using the tool input and output metadata as supplied by the tool wrapper XML, in a similar way that tardis uses command-line markup. All that the tardis command-line-markup is providing, is annotation of the command - i.e. which arguments represent input and output, and what are the respective data-types - so that the command and data can be factorised into split-command and split-data. But when the command is embedded in galaxy, that annotation is already supplied by the XML tool config. Therefore it should be possible to incorporate something like the tardis command and data factorisation approach, into the galaxy tool-config interpreter engine, with the required annotation provided by the tool-xml, rather than command-line markup. (....a switch in tool-config.xml for each tool would control whether parallelisation / job splitting was to be enabled for a given tool. If enabled, then 2 or 3 additional user input fields would be generated for the tool UI (e.g. parallelise or not ? chunksize ? and I include an option for randomly sampling the input there as well as its a handy place to put it); and then on submission the engine would factorise the job into splits, with a supervisor similar in function to tardis handling job submission to the cluster and output collation.) > > Like I said though, I would be eager for the platform itself to support > alternatives models of interaction between the Galaxy, Jobs, Tools, > Parallelism, etc... One of the really nice things about the tardis approach is > that it seems very self contained and all at the tool level, so you should be > able to create tardis tools pretty easily, use them inside a normal Galaxy > instance, and distribute them on the tool shed. thanks for the feedback ! I'll have a think about that approach as well - i.e. tardifying tools and putting these in the tool shed. This is what I am doing internally, with the tardified tools in our local tool shed. > > I hope this is reasonable and we can find ways to collaborate even if we don't > agree on every single point :). > > -John > Thanks again for looking at this and your encouraging comments. I probably won't make all that much progress with the "put it in the galaxy engine" idea for a while - but thats a potential road map I had thought of . In the near future I need to tidy up a few things, such as getting tardis to use drmaa. I'm also continuing to "tardify" a few tools for which thats useful for us , using the current galaxy-embedding hack, to get some processing done and also as further test cases. Usually each one flushes out another bug or two. Cheers Alan > -----Original Message----- > From: jmchil...@gmail.com [mailto:jmchil...@gmail.com] On Behalf Of > John Chilton > Sent: Thursday, 14 November 2013 9:56 a.m. > To: McCulloch, Alan > Cc: email@example.com > Subject: Re: [galaxy-dev] tardis job splitter > > On Mon, Oct 28, 2013 at 9:39 PM, McCulloch, Alan > <alan.mccull...@agresearch.co.nz> wrote: > > dear all, > > > > > > > > There have been a few posts lately about doing distributed computing > > via Galaxy – i.e. > > > > job splitters etc – below a contribution of some ideas we have > > developed > > > > and applied in our work, where we have arranged for some Galaxy tools > > to execute in parallel > > > > on our cluster. > > > > > > > > We have developed a job-splitter script "tardis.py" (available from > > > > https://bitbucket.org/agr-bifo/tardis), which takes marked-up > > > > standard unix commands that run an application or tool. The mark-up is > > > > prefixed to the input and output command-line options. Tardis strips > > off the > > > > mark-up, and re-writes the commands to refer to split inputs and > > outputs, which are then > > > > executed in parallel e.g. on a distributed compute resource. Tardis > > knows > > > > the output files to expect and how to join them back together. > > > > > > > > (This was referred to in our GCC2013 talk > > > > > http://wiki.galaxyproject.org/Events/GCC2013/Abstracts#Events.2FGCC201 > > 3.2FAbstracts.2FTalks.A_layered_genotyping-by-sequencing_pipeline_usin > > g_Galaxy > > ) > > > > > > > > Any reasonable unix based data processing or analysis command may be > > marked up and run > > > > using tardis, though of course tardis needs to know how to split and > > join the data. Our approach > > > > also assumes a “symmetrical” HPC cluster configuration, in the sense > > that each node sees the same > > > > view of the file system (and has the required underlying application > > installed). We use tardis > > > > to support both Galaxy and command-line based compute. > > > > > > > > Background / design pattern / motivating analogy: Galaxy provides a > > high level > > > > "end to end" view of a workflow; the HPC cluster resource that one > > uses then involves > > > > spraying chunks of data out into parallel processes, usually in the > > form of some kind of > > > > distributed compute cluster - but an end-user looking at a Galaxy > > history, should ideally not be able > > > > to tell whether the workflow was run as a single process on the > > server, or > > > > via many parallel processes on the cluster (apart from the fact that > > when run > > > > in parallel on the cluster, its alot faster!). We noticed that the > > TCP / IP layered networking > > > > protocol stack provides a useful metaphor and design pattern - with > > the "end to end" topology > > > > of a Galaxy workflow corresponding to the transport layer of TCP/ IP; > > and the distribution > > > > of computation across a cluster corresponding to the next TCP/IP > > layer down > > - the packet-routing > > > > layer. > > > > > > > > This picture suggested a strongly layered approach to provisioning > > > > Galaxy with parallelised compute on split data, and hence to an > > approach in which the > > > > footprint in the Galaxy code-base, of parallel / distributed compute > > support, should ideally > > > > (from the layered-design point of view) be minimal and superficial. > > Thus in our approach so far, > > > > the only footprint is in the tool config files, where we arrange the > > templating to > > > > (optionally) prefix the required tardis mark-up to the input and > > output command options, and > > > > the tardis script name to the command as a whole. tardis then takes > > care of rewriting and > > > > launching all of the jobs, and finally joining the results back > > together and putting them where > > > > galaxy expects them to be (and also housekeeping such as collating and > > passing up stderr and stdout , and > > > > appropriate process exit codes). (For each galaxy job, tardis creates > > a working folder in a designated > > > > scratch area, where input files are uncompressed and split; job files > > and their output > > > > are stored; logging is done etc. Split data is cleaned up at the end > > unless there > > > > was an error in some part of the job, in which case everything is > > retained > > > > for debugging and in some cases restart) > > > > > > > > (We modify Galaxy tool-configs so that the user can optionally choose > > to run > > > > the tool on our HPC cluster - there are three HPC related input > > fields, appended > > > > to the input section of a tool. Here the user selects whether they > > want to use > > > > our cluster and if so, they specify the chunk size, and can also at > > that point > > > > specify a sampling rate, since we often find it useful to be able to > > run preliminary > > > > analyses on a random sample of (for example) single or paired-end NGS > > sequence > > > > data, to obtain a fairly quick snapshot of the data, before the > > expense of a > > > > complete run. We found it convenient to include support for input > > sampling > > > > in tardis). > > > > > > > > The pdf document at https://bitbucket.org/agr-bifo/tardis includes a > > number of > > > > examples of marking up a command, and also a simple example of a > > galaxy tool-config that > > > > has been modified to include support for optionally running the job on > > our HPC cluster > > > > via the tardis pre-processor. > > > > > > > > Known limitations: > > > > > > > > * we have not yet attempted to integrate our approach with the > > existing Galaxy job-splitting > > > > distributed compute support, partly because of our “layered” design > > goal (admittedly also partly > > > > because of ignorance about its details ! ) > > > > > > > > * our current implementation is quite naive in the distributed compute > > API > > > > it uses - it supports launching condor job files (and also native > > sub-processes) - our plan > > > > is to replace that with using the drmaa API > > > > > > > > * we would like to integrate it better with the galaxy type system, > > probably via > > > > a galaxy-tardis wrapper > > > > > > > > We would be keen to contribute our approach to Galaxy if people are > > > > interested. ___________________________________________________________ Please keep all replies on the list by using "reply all" in your mail client. 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