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annotate distributedTest.jl @ 147:aa18b7bf4926 parallel_test

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Changed to initialize u and v as distributed arrays
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Mon, 25 Feb 2019 17:21:07 +0100
parents 21b188f38358
children 95a3ba70bccb
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1 @everywhere using Distributed
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2 @everywhere using DistributedArrays
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3
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4 # TODO: Currently uses integer division to calculate the local grid size.
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5 # Should we make sure this is handled in some way if mod(sz./nworkers()) != 0
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6 # or keep assertions?
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7 @everywhere function create_partitioned_grid(size::NTuple{Dim, Int}, limit_lower::NTuple{Dim, T}, limit_upper::NTuple{Dim, T}, nworkers_per_dim::NTuple{Dim, Int}) where Dim where T
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8 @assert mod.(size, nworkers_per_dim) == (0,0)
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9 @assert prod(nworkers_per_dim) == nworkers()
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10 # Translate the current worker id to a cartesian index, based on nworkers_per_dim
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11 ci = CartesianIndices(nworkers_per_dim);
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12 id = Tuple(ci[myid()-1])
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13
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14 # Compute the size of each partitioned grid
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15 size_partition = size./nworkers_per_dim
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16 size_partition = map(x->Int(x),size_partition) # TODO: Cant this be done in an easier way?...
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17 # Compute domain size for each partition
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18 domain_size = limit_upper.-limit_lower
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19 domain_partition_size = domain_size./nworkers_per_dim
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20
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21 # Compute the lower and upper limit for each grid partition, then construct the grid
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22 ll_partition = limit_lower .+ domain_partition_size.*(id.-1)
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23 lu_partition = limit_lower .+ domain_partition_size.*id
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24 grid = sbp.Grid.EquidistantGrid(size_partition, ll_partition, lu_partition)
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25 return grid
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26 end
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27
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28 # Create grid
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29 gridsize = (10000, 10000);
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30 limit_lower = (0., 0.)
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31 limit_upper = (2pi, 3pi/2)
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32 # TODO: Currently only works with same number of processes in each direction and for
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33 # an even number of processes
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34 nworkers_per_dim = (Int(nworkers()/2),Int(nworkers()/2))
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35 grids_partitioned = [@spawnat p create_partitioned_grid(gridsize, limit_lower , limit_upper, nworkers_per_dim) for p in workers()]
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36
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37 # Create Laplace operator
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38 @everywhere op = sbp.readOperator("d2_4th.txt","h_4th.txt")
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39 Laplace_partitioned = [@spawnat p sbp.Laplace(fetch(grids_partitioned[p-1]), 1.0, op) for p in workers()]
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40
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41 # Create initial value grid function v and solution grid function u
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42 @everywhere init(x,y) = sin(x) + sin(y)
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43 v = dzeros(gridsize)
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44 u = dzeros(gridsize)
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45 @async([@spawnat p v[:L] = sbp.Grid.evalOn(fetch(grids_partitioned[p-1]), init) for p in workers()]) #TODO: Correct use of async?
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47 # Apply Laplace
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48 @async([@spawnat p sbp.apply_tiled!(fetch(Laplace_partitioned[p-1]),u[:L], v[:L]) for p in workers()]) #TODO: Correct use of async?
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49
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50 @show maximum(abs.(u + v))