Hi all- I am trying to load a file of functions on a cluster of computers. In the past, I used require() (now depreciated) and the sendto() function described here <http://stackoverflow.com/questions/27677399/julia-how-to-copy-data-to-another-processor-in-julia>to make a data variable available on all workers. ( Note that I cannot simply load the data upon initializing the program because the data will change outside of the module, eventually receiving a stream of data from another program. So speed and flexibility is imperative). As recommended here <https://groups.google.com/forum/#!searchin/julia-users/$20require/julia-users/6zBKw4nd20I/5JLt7Ded0zkJ>, I defined a module containing the functions and used "using MyModule" to send it to the available workers. It seems that the major limitation of this approach is that data is not available to the functions within the module when using sendto(). I suspect this is because modules are encapsulated from other variables and functions. Bearing that in mind:
1. Is there a way around this problem using the module method? 2. Alternatively, is there a way I can make the functions and packages available to the workers without using modules? Perhaps something akin to the old require method? 3. Or is there a way to send the data via map() along with my function and distributed array? Essentially, my code loads stored inputs for numerous kernel density functions and converts them to a distributed array of arrays. For example: map(EvalKDFs,MyDistArray) Each time the above function is called, "MyData" needs to be available to the function EvalKDFs. However, map(EvalKDFs,MyDistArray,MyData) does not work because there is one array of data and many arrays within MyDistArray. I might be able to post a stripped down version of my code if my description does not suffice. Any help would be greatly appreciated.
