Repository URL to install this package:
|
Version:
3.0.0.dev0 ▾
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"""This is the script for `ray clusterbenchmark`."""
import time
import numpy as np
import ray
from ray.cluster_utils import Cluster
def main():
cluster = Cluster(
initialize_head=True,
connect=True,
head_node_args={"object_store_memory": 20 * 1024 * 1024 * 1024, "num_cpus": 16},
)
cluster.add_node(
object_store_memory=20 * 1024 * 1024 * 1024, num_gpus=1, num_cpus=16
)
object_ref_list = []
for i in range(0, 10):
object_ref = ray.put(np.random.rand(1024 * 128, 1024))
object_ref_list.append(object_ref)
@ray.remote(num_gpus=1)
def f(object_ref_list):
diffs = []
for object_ref in object_ref_list:
before = time.time()
ray.get(object_ref)
after = time.time()
diffs.append(after - before)
time.sleep(1)
return np.mean(diffs), np.std(diffs)
time_diff, time_diff_std = ray.get(f.remote(object_ref_list))
print(
"latency to get an 1G object over network",
round(time_diff, 2),
"+-",
round(time_diff_std, 2),
)
ray.shutdown()
cluster.shutdown()
if __name__ == "__main__":
main()