Jiajun Yao d63b152e9c [Core] Fix the ray_tasks{State="PENDING_ARGS_FETCH"} metric counting (#47770) 3 周之前
..
distributed 2c5745fcea [Release] Use with clause to make sure result json file is closed properly (#46484) 3 月之前
object_store d63b152e9c [Core] Fix the ray_tasks{State="PENDING_ARGS_FETCH"} metric counting (#47770) 3 周之前
single_node 2c5745fcea [Release] Use with clause to make sure result json file is closed properly (#46484) 3 月之前
README.md f28428e9ca [core] Update the scalability envelop (#32131) 1 年之前
app_config.yaml 25cf1842da [ci/release] Remove `default` images in app config templates (#37970) 1 年之前
distributed.yaml 549527687f Migrate scalability tests (#22901) 2 年之前
distributed_gce.yaml cb59e59ac5 Add GCE variation for core release tests [3/n] (#34425) 1 年之前
distributed_smoke_test.yaml 549527687f Migrate scalability tests (#22901) 2 年之前
many_nodes.yaml c6427d4186 Revert "[cost-reduction] reduce both the time and machine cost for test_many_tasks" (#29107) 2 年之前
many_nodes_gce.yaml a8261c84bd [CI] Add GCE variation for core release tests [1/n] (#34065) 1 年之前
object_store.yaml 2c2d96eeb1 [Nightly tests] Improve k8s testing (#23108) 2 年之前
object_store_gce.yaml cb59e59ac5 Add GCE variation for core release tests [3/n] (#34425) 1 年之前
scheduling.yaml 1483c4553c use smaller instance for scheduling tests (#25635) 2 年之前
scheduling_gce.yaml 225f6e1621 [Release Test] Add GCE variation for core release tests [4/n] (#34442) 1 年之前
single_node.yaml 1a0989a1c0 [Release Test] Add GCE variation for core release tests [2/n] (#34337) 1 年之前
single_node_gce.yaml 1a0989a1c0 [Release Test] Add GCE variation for core release tests [2/n] (#34337) 1 年之前

README.md

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) 2k+
# actors in cluster (with trivial workload) 40k+
# 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+