Support concurrent Actor calls in Ray (#6053)

python/ray/ray_perf.py

@@ -142,14 +142,28 @@ def main():
     def actor_sync():
         ray.get(a.small_value.remote())
 
-    timeit("single client actor calls sync", actor_sync)
+    timeit("1:1 actor calls sync", actor_sync)
 
     a = Actor.remote()
 
     def actor_async():
         ray.get([a.small_value.remote() for _ in range(1000)])
 
-    timeit("single client actor calls async", actor_async, 1000)
+    timeit("1:1 actor calls async", actor_async, 1000)
+
+    a = Actor.options(is_direct_call=True).remote()
+
+    def actor_concurrent():
+        ray.get([a.small_value.remote() for _ in range(1000)])
+
+    timeit("1:1 direct actor calls async", actor_concurrent, 1000)
+
+    a = Actor.options(is_direct_call=True, max_concurrency=16).remote()
+
+    def actor_concurrent():
+        ray.get([a.small_value.remote() for _ in range(1000)])
+
+    timeit("1:1 direct actor calls concurrent", actor_concurrent, 1000)
 
     n_cpu = multiprocessing.cpu_count() // 2
     a = [Actor.remote() for _ in range(n_cpu)]
@@ -161,7 +175,7 @@ def main():
     def actor_multi2():
         ray.get([work.remote(a) for _ in range(m)])
 
-    timeit("multi client actor calls async", actor_multi2, m * n)
+    timeit("n:n actor calls async", actor_multi2, m * n)
 
     n = 5000
     n_cpu = multiprocessing.cpu_count() // 2
@@ -171,15 +185,24 @@ def main():
     def actor_async_direct():
         ray.get(client.small_value_batch.remote(n))
 
-    timeit("single client direct actor calls async", actor_async_direct,
-           n * len(actors))
+    timeit("1:n direct actor calls async", actor_async_direct, n * len(actors))
 
     clients = [Client.remote(a) for a in actors]
 
     def actor_multi2_direct():
         ray.get([c.small_value_batch.remote(n) for c in clients])
 
-    timeit("multi client direct actor calls async", actor_multi2_direct,
+    timeit("n:n direct actor calls async", actor_multi2_direct,
+           n * len(clients))
+
+    n = 1000
+    actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
+    clients = [Client.remote(a) for a in actors]
+
+    def actor_multi2_direct_arg():
+        ray.get([c.small_value_batch_arg.remote(n) for c in clients])
+
+    timeit("n:n direct actor calls with arg async", actor_multi2_direct_arg,
            n * len(clients))
 
     n = 1000