Shared Arrays

SharedArrays.SharedArray — Type

  1. SharedArray{T}(dims::NTuple; init=false, pids=Int[])
  2. SharedArray{T,N}(...)

Construct a SharedArray of a bits type T and size dims across the processes specified by pids - all of which have to be on the same host. If N is specified by calling SharedArray{T,N}(dims), then N must match the length of dims.

If pids is left unspecified, the shared array will be mapped across all processes on the current host, including the master. But, localindices and indexpids will only refer to worker processes. This facilitates work distribution code to use workers for actual computation with the master process acting as a driver.

If an init function of the type initfn(S::SharedArray) is specified, it is called on all the participating workers.

The shared array is valid as long as a reference to the SharedArray object exists on the node which created the mapping.

  1. SharedArray{T}(filename::AbstractString, dims::NTuple, [offset=0]; mode=nothing, init=false, pids=Int[])
  2. SharedArray{T,N}(...)

Construct a SharedArray backed by the file filename, with element type T (must be a bits type) and size dims, across the processes specified by pids - all of which have to be on the same host. This file is mmapped into the host memory, with the following consequences:

  • The array data must be represented in binary format (e.g., an ASCII format like CSV cannot be supported)

  • Any changes you make to the array values (e.g., A[3] = 0) will also change the values on disk

If pids is left unspecified, the shared array will be mapped across all processes on the current host, including the master. But, localindices and indexpids will only refer to worker processes. This facilitates work distribution code to use workers for actual computation with the master process acting as a driver.

mode must be one of "r", "r+", "w+", or "a+", and defaults to "r+" if the file specified by filename already exists, or "w+" if not. If an init function of the type initfn(S::SharedArray) is specified, it is called on all the participating workers. You cannot specify an init function if the file is not writable.

offset allows you to skip the specified number of bytes at the beginning of the file.

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SharedArrays.SharedVector — Type

  1. SharedVector

A one-dimensional SharedArray.

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SharedArrays.SharedMatrix — Type

  1. SharedMatrix

A two-dimensional SharedArray.

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Distributed.procs — Method

  1. procs(S::SharedArray)

Get the vector of processes mapping the shared array.

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SharedArrays.sdata — Function

  1. sdata(S::SharedArray)

Returns the actual Array object backing S.

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SharedArrays.indexpids — Function

  1. indexpids(S::SharedArray)

Returns the current worker’s index in the list of workers mapping the SharedArray (i.e. in the same list returned by procs(S)), or 0 if the SharedArray is not mapped locally.

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SharedArrays.localindices — Function

  1. localindices(S::SharedArray)

Returns a range describing the “default” indices to be handled by the current process. This range should be interpreted in the sense of linear indexing, i.e., as a sub-range of 1:length(S). In multi-process contexts, returns an empty range in the parent process (or any process for which indexpids returns 0).

It’s worth emphasizing that localindices exists purely as a convenience, and you can partition work on the array among workers any way you wish. For a SharedArray, all indices should be equally fast for each worker process.

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