Use 2xlarge instances in long running tests (#6802)

This commit is contained in:
Edward Oakes
2020-01-15 19:47:59 -06:00
committed by GitHub
parent c480d1d1e4
commit b750bd7fc9
10 changed files with 18 additions and 11 deletions
@@ -13,7 +13,7 @@ auth:
ssh_user: ubuntu
head_node:
InstanceType: m5.xlarge
InstanceType: m5.2xlarge
ImageId: ami-0888a3b5189309429 # DLAMI 7/1/19
BlockDeviceMappings:
- DeviceName: /dev/sda1
@@ -10,8 +10,7 @@ commands:
command: |
# Install nightly Ray wheels.
source activate tensorflow_p36 && pip install -U {{wheel}}
source activate tensorflow_p36 && pip install ray[rllib] ray[debug] gym[atari]
source activate tensorflow_p36 && pip install ray[debug]
source activate tensorflow_p36 && pip install ray[dashboard,debug,rllib,tune] gym[atari]
source activate tensorflow_p36 && python workloads/{{workload}}.py
params:
- name: wheel
@@ -28,7 +28,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
+2 -1
View File
@@ -25,7 +25,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
+2 -1
View File
@@ -25,7 +25,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
@@ -28,7 +28,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
@@ -27,7 +27,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 5},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
@@ -28,7 +28,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
@@ -26,7 +26,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.
+2 -1
View File
@@ -26,7 +26,8 @@ for i in range(num_nodes):
num_gpus=0,
resources={str(i): 2},
object_store_memory=object_store_memory,
redis_max_memory=redis_max_memory)
redis_max_memory=redis_max_memory,
webui_host="0.0.0.0")
ray.init(address=cluster.address)
# Run the workload.