ray/benchmarks
2021-06-22 11:24:21 +01:00
..
distributed [release] add release test output logs for tune (1.4.0) and core scalability envelope (1.4.1) 2021-06-22 11:24:21 +01:00
object_store [release] add release test output logs for tune (1.4.0) and core scalability envelope (1.4.1) 2021-06-22 11:24:21 +01:00
single_node [release] add release test output logs for tune (1.4.0) and core scalability envelope (1.4.1) 2021-06-22 11:24:21 +01:00
README.md Move scalability envelope back down to 250 nodes (#15381) 2021-04-16 19:39:24 -07:00

Ray Scalability Envelope

Distributed Benchmarks

All distributed tests are run on 64 nodes with 64 cores/node. Maximum number of nodes is achieved by adding 4 core nodes.

Dimension Quantity
# nodes in cluster (with trivial task workload) 250+
# actors in cluster (with trivial workload) 10k+
# simultaneously running tasks 10k+
# simultaneously running placement groups 1k+

Object Store Benchmarks

Dimension Quantity
1 GiB object broadcast (# of nodes) 50+

Single Node Benchmarks.

All single node benchmarks are run on a single m4.16xlarge.

Dimension Quantity
# of object arguments to a single task 10000+
# of objects returned from a single task 3000+
# of plasma objects in a single ray.get call 10000+
# of tasks queued on a single node 1,000,000+
Maximum ray.get numpy object size 100GiB+