Avoid the zeros(nthreads())[threadid()] buffering pattern (JuliaGra…

…phs#293)

* Avoid the `zeros(nthreads())[threadid()]` buffering pattern

* Fix partitioning

src/Parallel/centrality/betweenness.jl

@@ -98,25 +98,26 @@ function threaded_betweenness_centrality(
     k = length(vs)
     isdir = is_directed(g)
 
-    local_betweenness = [zeros(n_v) for i in 1:nthreads()]
     vs_active = findall((x) -> degree(g, x) > 0, vs) # 0 might be 1?
+    k_active = length(vs_active)
+    d, r = divrem(k_active, Threads.nthreads())
+    ntasks = d == 0 ? r : Threads.nthreads()
+    local_betweenness = [zeros(n_v) for _ in 1:ntasks]
+    task_size = cld(k_active, ntasks)
 
-    Base.Threads.@threads for s in vs_active
-        state = Graphs.dijkstra_shortest_paths(
-            g, s, distmx; allpaths=true, trackvertices=true
-        )
-        if endpoints
-            Graphs._accumulate_endpoints!(
-                local_betweenness[Base.Threads.threadid()], state, g, s
-            )
-        else
-            Graphs._accumulate_basic!(
-                local_betweenness[Base.Threads.threadid()], state, g, s
+    @sync for (t, task_range) in enumerate(Iterators.partition(1:k_active, task_size))
+        Threads.@spawn for s in @view(vs_active[task_range])
+            state = Graphs.dijkstra_shortest_paths(
+                g, s, distmx; allpaths=true, trackvertices=true
             )
+            if endpoints
+                Graphs._accumulate_endpoints!(local_betweenness[t], state, g, s)
+            else
+                Graphs._accumulate_basic!(local_betweenness[t], state, g, s)
+            end
         end
     end
     betweenness = reduce(+, local_betweenness)
-
     Graphs._rescale!(betweenness, n_v, normalize, isdir, k)
 
     return betweenness

src/Parallel/centrality/stress.jl

@@ -44,14 +44,17 @@ function threaded_stress_centrality(g::AbstractGraph, vs=vertices(g))::Vector{In
     isdir = is_directed(g)
 
     # Parallel reduction
-    local_stress = [zeros(Int, n_v) for _ in 1:nthreads()]
+    d, r = divrem(k, Threads.nthreads())
+    ntasks = d == 0 ? r : Threads.nthreads()
+    local_stress = [zeros(Int, n_v) for _ in 1:ntasks]
+    task_size = cld(k, ntasks)
 
-    Base.Threads.@threads for s in vs
-        if degree(g, s) > 0  # this might be 1?
-            state = Graphs.dijkstra_shortest_paths(g, s; allpaths=true, trackvertices=true)
-            Graphs._stress_accumulate_basic!(
-                local_stress[Base.Threads.threadid()], state, g, s
-            )
+    @sync for (t, task_range) in enumerate(Iterators.partition(1:k, task_size))
+        Threads.@spawn for s in @view(vs[task_range])
+            if degree(g, s) > 0  # this might be 1?
+                state = Graphs.dijkstra_shortest_paths(g, s; allpaths=true, trackvertices=true)
+                Graphs._stress_accumulate_basic!(local_stress[t], state, g, s)
+            end
         end
     end
     return reduce(+, local_stress)

src/Parallel/utils.jl

@@ -40,20 +40,24 @@ Multi-threaded implementation of [`generate_reduce`](@ref).
 function threaded_generate_reduce(
     g::AbstractGraph{T}, gen_func::Function, comp::Comp, reps::Integer
 ) where {T<:Integer,Comp}
-    n_t = Base.Threads.nthreads()
-    is_undef = ones(Bool, n_t)
-    min_set = [Vector{T}() for _ in 1:n_t]
-    Base.Threads.@threads for _ in 1:reps
-        t = Base.Threads.threadid()
-        next_set = gen_func(g)
-        if is_undef[t] || comp(next_set, min_set[t])
-            min_set[t] = next_set
-            is_undef[t] = false
+    d, r = divrem(reps, Threads.nthreads())
+    ntasks = d == 0 ? r : Threads.nthreads()
+    min_set = [Vector{T}() for _ in 1:ntasks]
+    is_undef = ones(Bool, ntasks)
+    task_size = cld(reps, ntasks)
+
+    @sync for (t, task_range) in enumerate(Iterators.partition(1:reps, task_size))
+        Threads.@spawn for _ in task_range
+            next_set = gen_func(g)
+            if is_undef[t] || comp(next_set, min_set[t])
+                min_set[t] = next_set
+                is_undef[t] = false
+            end
         end
     end
 
     min_ind = 0
-    for i in filter((j) -> !is_undef[j], 1:n_t)
+    for i in filter((j) -> !is_undef[j], 1:ntasks)
         if min_ind == 0 || comp(min_set[i], min_set[min_ind])
             min_ind = i
         end