python - IPython parallel computing vs pyzmq for cluster computing -

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I am currently working on some simulation code written in C, which runs on various remote machines. When the part is finished, I want to expand my work with Python simulation API and any type of job-queue system, which should do the following:

1. Specify a set of parameters

3. Remove the result of hosting the computer

I had a look at different structures to complete this task and My first choice came down to iPython Parallel, I took a look at the documentation and it seems easy to experiment with the tests I did.

  • That means if the ipcontroller crashes, my job queue has gone?
  • What happens if a remote machine crashes? Is there any type of error handling?

Since I run a longer simulation (1-2 weeks) I do not want my simulation to fail if a part of the system crashes. So could there be any way to deal with iPyathon equally? Parallel?

My second method would be to use POSCAC and implement jobs from scratch. In this situation, what would be the best zmq-pattern for this situation?

And last but not least, is there a better framework for this scenario?

The lie behind the curtain is a bit more complex view, how (parallel) number-crunching To organize the work-package flow along with the pipeline (s) as well.

or

CPU-Core-Week (s),

or

Being a work-package of work over some hundred thousand CPU-core hours , theories are the same and follow common knowledge.

Key Features

    All computing performance of resources (ideally one linear one) Level Capacity
  • )
  • viable / TCO cost of access (upfront cum $ SS, recurring cum $ ts, $ co-$ ts, $ $ peed with $ ts)

Approach to solution Home

  • Home-bro architecture for distributed large scale parallel scheduler <

  • Reuse the available grid-based computing resources

ParameterSetVectorSPACE (which can not be understood in any trivial GPU parallel scheme), the selection of the second approach has been certified to be more productive, rather than just burning dozens of people in each other Tried one wheel

Due to being in the academic environment, there can be an easy way to get acceptable access to resource-pool (A) to process the work-pack, whereas commercial institutions can achieve only one, B. Ased based on the limitations of your acceptable budget

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