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Merge branch 'master' of github.com:gridap/GridapDistributed.jl into …
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JordiManyer committed Aug 6, 2024
2 parents 4b0d45d + 333675d commit 1db4a82
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6 changes: 6 additions & 0 deletions NEWS.md
Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,12 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## Unreleased

### Fixed

- Fixed distributed interpolators for Vector-Valued FESpaces. Since PR[#152](https://github.com/gridap/GridapDistributed.jl/pull/152).

## [0.4.3] 2024-07-18

### Added
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118 changes: 72 additions & 46 deletions src/CellData.jl
Original file line number Diff line number Diff line change
Expand Up @@ -355,73 +355,99 @@ f(s) instead of s(f)?
end

# Interpolation at arbitrary points (returns -Inf if the point is not found)
Arrays.evaluate!(cache,f::DistributedCellField,x::Point) = evaluate!(cache,Interpolable(f),x)
Arrays.evaluate!(cache,f::DistributedCellField,x::AbstractVector{<:Point}) = evaluate!(cache,Interpolable(f),x)
Arrays.evaluate!(cache,f::DistributedCellField,x::Point) = evaluate(Interpolable(f),x)
Arrays.evaluate!(cache,f::DistributedCellField,x::AbstractVector{<:Point}) = evaluate(Interpolable(f),x)

struct DistributedInterpolable{A} <: Function
struct DistributedInterpolable{Tx,Ty,A} <: Function
interps::A
function DistributedInterpolable(interps::AbstractArray{<:Interpolable})
Tx,Ty = map(interps) do I
fi = I.uh
trian = get_triangulation(fi)
x = mean(testitem(get_cell_coordinates(trian)))
return typeof(x), return_type(fi,x)
end |> tuple_of_arrays
Tx = getany(Tx)
Ty = getany(Ty)
A = typeof(interps)
new{Tx,Ty,A}(interps)
end
end

local_views(a::DistributedInterpolable) = a.interps

function Interpolable(f::DistributedCellField;kwargs...)
interps = map(local_views(f)) do fun
Interpolable(fun,kwargs...)
interps = map(local_views(f)) do f
Interpolable(f,kwargs...)
end
DistributedInterpolable(interps)
end

(a::DistributedInterpolable)(x) = evaluate(a,x)

function Gridap.Arrays.return_cache(I::DistributedInterpolable,x::Point)
caches = map(local_views(I)) do fi
trian = get_triangulation(fi.uh)
y=mean(testitem(get_cell_coordinates(trian)))
@check typeof(testitem(x)) == typeof(y) "Can only evaluate DistributedInterpolable at physical points of the same dimension of the underlying triangulation"
return_cache(fi,y)
Arrays.return_cache(f::DistributedInterpolable,x::Point) = return_cache(f,[x])
Arrays.evaluate!(caches,I::DistributedInterpolable,x::Point) = first(evaluate!(caches,I,[x]))

function Arrays.return_cache(I::DistributedInterpolable{Tx,Ty},x::AbstractVector{<:Point}) where {Tx,Ty}
msg = "Can only evaluate DistributedInterpolable at physical points of the same dimension of the underlying triangulation"
@check Tx == eltype(x) msg
caches = map(local_views(I)) do I
trian = get_triangulation(I.uh)
y = mean(testitem(get_cell_coordinates(trian)))
return_cache(I,y)
end
caches
caches
end
Gridap.Arrays.return_cache(f::DistributedInterpolable,x::AbstractVector{<:Point}) = Gridap.Arrays.return_cache(f,testitem(x))

function Gridap.Arrays.evaluate!(caches,I::DistributedInterpolable,x::Point)
y=map(local_views(I),local_views(caches)) do fi,cache
function Arrays.evaluate!(cache,I::DistributedInterpolable{Tx,Ty},x::AbstractVector{<:Point}) where {Tx,Ty}
_allgather(x) = PartitionedArrays.getdata(getany(gather(x;destination=:all)))

# Evaluate in local portions of the domain. Only keep points inside the domain.
nx = length(x)
my_ids, my_vals = map(local_views(I),local_views(cache)) do I, cache
ids = Vector{Int}(undef,nx)
vals = Vector{Ty}(undef,nx)
k = 1
yi = zero(Ty)
for (i,xi) in enumerate(x)
inside = true
try
evaluate!(cache,fi,x)
yi = evaluate!(cache,I,xi)
catch
-Inf
inside = false
end
end
# reduce(max,y)
z=gather(y)
map_main(local_views(z)) do zi
reduce(max,zi)
end
end

function Gridap.Arrays.evaluate!(caches,I::DistributedInterpolable,v::AbstractVector{<:Point})
n=length(local_views(I))
m=length(v)
y=map(local_views(I),local_views(caches)) do fi,cache
w=Vector{Float64}(undef,m)
for (i,x) in enumerate(v)
try
w[i]=evaluate!(cache,fi,x)
catch
w[i]=-Inf
end
if inside
ids[k] = i
vals[k] = yi
k += 1
end
return w
end
# z=gather(y,destination=:all)
z=gather(y)
map_main(local_views(z)) do zi
w=Vector{Float64}(undef,m)
for i=0:m-1
w[i+1]=reduce(max,zi.data[zi.ptrs[1:n].+i])
end
return w
resize!(ids,k-1)
resize!(vals,k-1)
return ids, vals
end |> tuple_of_arrays

# Communicate results, so that every (id,value) pair is known by every process
if Ty <: VectorValue
D = num_components(Ty)
vals_d = Vector{Vector{eltype(Ty)}}(undef,D)
for d in 1:D
my_vals_d = map(y_p -> map(y_p_i -> y_p_i[d],y_p),my_vals)
vals_d[d] = _allgather(my_vals_d)
end
# reduce((v,w)->broadcast(max,v,w),y)
vals = map(VectorValue,vals_d...)
else
vals = _allgather(my_vals)
end
ids = _allgather(my_ids)

# Combine results
w = Vector{Ty}(undef,nx)
for (i,v) in zip(ids,vals)
w[i] = v
end

return w
end

# Support for distributed Dirac deltas
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26 changes: 16 additions & 10 deletions test/CellDataTests.jl
Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ function main(distribute,parts)
u3 = CellField(2.0,Ω)
u = _my_op(u1,u2,u3)

order = 1
order = 1
reffe = ReferenceFE(lagrangian,Float64,order)
V = TestFESpace(model,reffe)
uh = interpolate_everywhere(x->x[1]+x[2],V)
Expand All @@ -67,15 +67,21 @@ function main(distribute,parts)
x3 = Point(0.9,0.9)
v = [x1,x2,x3]

u1 = uh(x1)
u2 = uh(x2)
uv = uh(v)
@test uh(x1) == 0.2
@test uh(x2) == 1.0
@test uh(v) == [0.2,1.0,1.8]

map_main(u1,u2,uv) do u1,u2,v
@test u1 == 0.2
@test u2 == 1.0
@test v ==[0.2,1.0,1.8]
end
reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order)
V = TestFESpace(model,reffe)
uh = interpolate_everywhere(x->x,V)
x1 = Point(0.1,0.1)
x2 = Point(0.1,0.9)
x3 = Point(0.9,0.9)
v = [x1,x2,x3]

@test uh(x1) == x1
@test uh(x2) == x2
@test uh(v) == v

# Point δ
δ=DiracDelta{0}(model;tags=2)
Expand All @@ -89,7 +95,7 @@ function main(distribute,parts)
@test sum(δ(f)) 8.0
@test sum(δ(3.0)) 12.0
@test sum(δ(x->2*x)) VectorValue(16.0,0.0)

end

end # module

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