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https://github.com/vale981/ray
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distributed | ||
object_store | ||
single_node | ||
app_config.yaml | ||
benchmark_tests.yaml | ||
distributed.yaml | ||
distributed_smoke_test.yaml | ||
many_nodes.yaml | ||
object_store.yaml | ||
README.md | ||
single_node.yaml |
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+ |