1 files changed, 60 insertions, 0 deletions
diff --git a/tests/parallel/tconvexhull.nim b/tests/parallel/tconvexhull.nim
new file mode 100644
index 000000000..a89aa910b
--- /dev/null
+++ b/tests/parallel/tconvexhull.nim
@@ -0,0 +1,60 @@
+discard """
+  matrix: "--mm:refc"
+  output: '''
+'''
+"""
+
+# parallel convex hull for Nim bigbreak
+# nim c --threads:on -d:release pconvex_hull.nim
+import algorithm, sequtils, threadpool
+
+type Point = tuple[x, y: float]
+
+proc cmpPoint(a, b: Point): int =
+  result = cmp(a.x, b.x)
+  if result == 0:
+    result = cmp(a.y, b.y)
+
+template cross[T](o, a, b: T): untyped =
+  (a.x - o.x) * (b.y - o.y) - (a.y - o.y) * (b.x - o.x)
+
+template pro(): untyped =
+  while lr1 > 0 and cross(result[lr1 - 1], result[lr1], p[i]) <= 0:
+    discard result.pop
+    lr1 -= 1
+  result.add(p[i])
+  lr1 += 1
+
+proc half[T](p: seq[T]; upper: bool): seq[T] =
+  var i, lr1: int
+  result = @[]
+  lr1 = -1
+  if upper:
+    i = 0
+    while i <= high(p):
+      pro()
+      i += 1
+  else:
+    i = high(p)
+    while i >= low(p):
+      pro()
+      i -= 1
+  discard result.pop
+
+proc convex_hull[T](points: var seq[T], cmp: proc(x, y: T): int {.closure.}) : seq[T] =
+  if len(points) < 2: return points
+  points.sort(cmp)
+  var ul: array[2, FlowVar[seq[T]]]
+  parallel:
+    for k in 0..ul.high:
+      ul[k] = spawn half[T](points, k == 0)
+  result = concat(^ul[0], ^ul[1])
+
+var s = map(toSeq(0..9999), proc(x: int): Point = (float(x div 100), float(x mod 100)))
+# On some runs, this pool size reduction will set the "shutdown" attribute on the
+# worker thread that executes our spawned task, before we can read the flowvars.
+setMaxPoolSize 2
+
+for i in 0..2:
+  doAssert convex_hull[Point](s, cmpPoint) ==
+      @[(0.0, 0.0), (99.0, 0.0), (99.0, 99.0), (0.0, 99.0)]