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comparison distributedTest.jl @ 148:95a3ba70bccb parallel_test

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Added some clarifying comments on the state of distributedTest.jl
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Tue, 26 Feb 2019 10:02:20 +0100
parents aa18b7bf4926
children 11b6646918d4
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147:aa18b7bf4926 148:95a3ba70bccb
1 @everywhere using Distributed 1 #NOTE: The followig code "works" in that the resulting error is small. Much more
2 # work needs to be done in order to figure out how julias distributed parallelism works
3 # especially w.r.t data movement.
4
5 #TODO: everywhere using here or just everywhere include?
2 @everywhere using DistributedArrays 6 @everywhere using DistributedArrays
3 7
4 # TODO: Currently uses integer division to calculate the local grid size. 8 # TODO: Currently uses integer division to calculate the local grid size.
5 # Should we make sure this is handled in some way if mod(sz./nworkers()) != 0 9 # Should we make sure this is handled in some way if mod(sz./nworkers()) != 0
6 # or keep assertions? 10 # or keep assertions?
24 grid = sbp.Grid.EquidistantGrid(size_partition, ll_partition, lu_partition) 28 grid = sbp.Grid.EquidistantGrid(size_partition, ll_partition, lu_partition)
25 return grid 29 return grid
26 end 30 end
27 31
28 # Create grid 32 # Create grid
33 #TODO: Should these be declared globally?
29 gridsize = (10000, 10000); 34 gridsize = (10000, 10000);
30 limit_lower = (0., 0.) 35 limit_lower = (0., 0.)
31 limit_upper = (2pi, 3pi/2) 36 limit_upper = (2pi, 3pi/2)
37 nworkers_per_dim = (Int(nworkers()/2),Int(nworkers()/2))
38
32 # TODO: Currently only works with same number of processes in each direction and for 39 # TODO: Currently only works with same number of processes in each direction and for
33 # an even number of processes 40 # an even number of processes
34 nworkers_per_dim = (Int(nworkers()/2),Int(nworkers()/2))
35 grids_partitioned = [@spawnat p create_partitioned_grid(gridsize, limit_lower , limit_upper, nworkers_per_dim) for p in workers()] 41 grids_partitioned = [@spawnat p create_partitioned_grid(gridsize, limit_lower , limit_upper, nworkers_per_dim) for p in workers()]
36 42
37 # Create Laplace operator 43 # Create Laplace operator
38 @everywhere op = sbp.readOperator("d2_4th.txt","h_4th.txt") 44 # TODO: If we dont have fetch here, then the error is large. Does this indicate that we need to move data, or simply that
39 Laplace_partitioned = [@spawnat p sbp.Laplace(fetch(grids_partitioned[p-1]), 1.0, op) for p in workers()] 45 # the future is not yet computed once this statement is reached?
46 Laplace_partitioned = [@spawnat p sbp.Laplace(fetch(grids_partitioned[p-1]), 1.0, sbp.readOperator("d2_4th.txt","h_4th.txt")) for p in workers()]
40 47
41 # Create initial value grid function v and solution grid function u 48 # Create initial value grid function v and solution grid function u
42 @everywhere init(x,y) = sin(x) + sin(y) 49 #TODO: Should init be declared globally?
43 v = dzeros(gridsize) 50 init(x,y) = sin(x) + sin(y)
44 u = dzeros(gridsize) 51 v = dzeros(gridsize) # Distribured arrays
45 @async([@spawnat p v[:L] = sbp.Grid.evalOn(fetch(grids_partitioned[p-1]), init) for p in workers()]) #TODO: Correct use of async? 52 u = dzeros(gridsize) # Distribured arrays
53 fetch([@spawnat p v[:L] = sbp.Grid.evalOn(fetch(grids_partitioned[p-1]), init) for p in workers()]) #TODO: Don't want to fetch here
46 54
47 # Apply Laplace 55 # Apply Laplace
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? 56 fetch([@spawnat p sbp.apply_tiled!(fetch(Laplace_partitioned[p-1]),u[:L], v[:L]) for p in workers()]) #TODO: Don't want to fetch here
49 57
58 #TODO: Here we need to make sure that the data is ready.
50 @show maximum(abs.(u + v)) 59 @show maximum(abs.(u + v))