def main(argv):
launch_instances = False
if len(argv) >= 1 and argv[0] == "True":
launch_instances = True
utilizations = [0.8, 0.9]
sample_ratios = [1, 1.1, 1.2, 1.5, 2.0, 3.0]
sample_ratio_constrained = 2
# Amount of time it takes each task to run in isolation
task_duration_ms = 100
tasks_per_job = 10
private_ssh_key = "patkey.pem"
sparrow_branch = "master"
nm_task_scheduler = "fifo"
num_backends = 100
num_frontends = 10
cores_per_backend = 8
# Run each trial for 5 minutes.
trial_length = 400
num_preferred_nodes = 0
num_users = 1
cluster = "probe"
full_utilization_rate_s = (float(num_backends * cores_per_backend * 1000) /
(task_duration_ms * tasks_per_job * num_frontends))
# Warmup information
warmup_s = 30
post_warmup_s = 30
warmup_arrival_rate_s = 0.4 * full_utilization_rate_s
if launch_instances:
print "********Launching instances..."
run_cmd("./ec2-exp.sh launch %s -f %s -b %s -i %s" % # --spot-price %s" %
(cluster, num_frontends, num_backends, private_ssh_key))
time.sleep(10)
for sample_ratio in sample_ratios:
for utilization in utilizations:
arrival_rate_s = utilization * full_utilization_rate_s
# This is a little bit of a hacky way to pass args to the ec2 script.
(opts, args) = ec2_exp.parse_args(False)
opts.identity_file = private_ssh_key
opts.arrival_rate = arrival_rate_s
opts.branch = sparrow_branch
opts.sample_ratio = sample_ratio
opts.sample_ratio_constrained = sample_ratio_constrained
opts.tasks_per_job = tasks_per_job
opts.num_preferred_nodes = num_preferred_nodes
opts.cpus = cores_per_backend
conn = boto.connect_ec2()
frontends, backends = ec2_exp.find_existing_cluster(conn, opts, cluster)
print ("********Launching experiment at utilization %s with sample ratio %s..." %
(utilization, sample_ratio))
print ("********Deploying with arrival rate %s and warmup arrival rate %s"
% (arrival_rate_s, warmup_arrival_rate_s))
ec2_exp.deploy_cluster(frontends, backends, opts, warmup_arrival_rate_s, warmup_s,
post_warmup_s, nm_task_scheduler)
ec2_exp.start_sparrow(frontends, backends, opts)
print "*******Sleeping after starting Sparrow"
time.sleep(10)
print "********Starting prototype frontends and backends"
ec2_exp.start_proto(frontends, backends, opts)
time.sleep(trial_length)
log_dirname = "/home/ec2-user/sparrow/deploy/ec2/probe_ratio_%s_%s" % (utilization, sample_ratio)
while os.path.exists(log_dirname):
log_dirname = "%s_a" % log_dirname
os.mkdir(log_dirname)
ec2_exp.execute_command(frontends, backends, opts, "./find_bugs.sh")
print "********Stopping prototypes and Sparrow"
ec2_exp.stop_proto(frontends, backends, opts)
ec2_exp.stop_sparrow(frontends, backends, opts)
print "********Collecting logs and placing in %s" % log_dirname
opts.log_dir = log_dirname
ec2_exp.collect_logs(frontends, backends, opts)
opts.arrival_rate = arrival_rate_s
opts.branch = sparrow_branch
opts.sample_ratio = sample_ratio
opts.sample_ratio_constrained = sample_ratio_constrained
opts.tasks_per_job = tasks_per_job
opts.num_preferred_nodes = num_preferred_nodes
conn = boto.connect_ec2()
frontends, backends = ec2_exp.find_existing_cluster(conn, opts)
print ("********Launching experiment at utilization %s with sample ratio %s..." %
(utilization, sample_ratio))
print ("********Deploying with arrival rate %s and warmup arrival rate %s"
% (arrival_rate_s, warmup_arrival_rate_s))
ec2_exp.deploy_cluster(frontends, backends, opts, warmup_arrival_rate_s, warmup_s,
post_warmup_s, num_users)
ec2_exp.start_sparrow(frontends, backends, opts)
print "*******Sleeping after starting Sparrow"
time.sleep(10)
print "********Starting prototype frontends and backends"
ec2_exp.start_proto(frontends, backends, opts)
time.sleep(trial_length)
log_dirname = "/disk1/sparrow/fairness_%s_%s" % (utilization, sample_ratio)
while os.path.exists(log_dirname):
log_dirname = "%s_a" % log_dirname
os.mkdir(log_dirname)
ec2_exp.execute_command(frontends, backends, opts, "./find_bugs.sh")
def main(argv):
launch_instances = False
if len(argv) >= 1 and argv[0] == "True":
launch_instances = True
utilization_user_pairs = [(0.25, "high:1:0"),
(0.5, "high:1:0,low:1:0"),
(0.75, "high:1:0,low:2:0"),
(1.0, "high:1:0,low:3:0"),
(1.25, "high:1:0,low:4:0"),
(1.5, "high:1:0,low:5:0"),
(1.75, "high:1:0,low:6:0"),
(2.0, "high:1:0,low:7:0")]
sample_ratios = [2.0]
sample_ratio_constrained = 1
# Amount of time it takes each task to run in isolation
task_duration_ms = 100
tasks_per_job = 1
private_ssh_key = "patkey.pem"
sparrow_branch = "debugging"
num_backends = 5
num_frontends = 1
cores_per_backend = 4
# Run each trial for 5 minutes.
trial_length = 500
num_preferred_nodes = 0
nm_task_scheduler = "priority"
cluster_name = "isolation"
full_utilization_rate_s = (float(num_backends * cores_per_backend * 1000) /
(task_duration_ms * tasks_per_job * num_frontends))
# Warmup information
warmup_s = 120
post_warmup_s = 30
warmup_arrival_rate_s = 0.4 * full_utilization_rate_s
if launch_instances:
print "********Launching instances..."
run_cmd(("./ec2-exp.sh launch %s --ami ami-a658c0cf " +
"--instance-type cr1.8xlarge --spot-price %s -f %s -b %s -i %s") %
(cluster_name, 0.5, num_frontends, num_backends, private_ssh_key))
time.sleep(10)
for sample_ratio in sample_ratios:
for utilization, users in utilization_user_pairs:
arrival_rate_s = utilization * full_utilization_rate_s
# This is a little bit of a hacky way to pass args to the ec2 script.
(opts, args) = ec2_exp.parse_args(False)
opts.identity_file = private_ssh_key
opts.arrival_rate = arrival_rate_s
opts.branch = sparrow_branch
opts.sample_ratio = sample_ratio
opts.sample_ratio_constrained = sample_ratio_constrained
opts.tasks_per_job = tasks_per_job
opts.num_preferred_nodes = num_preferred_nodes
opts.cpus = cores_per_backend
conn = boto.connect_ec2()
frontends, backends = ec2_exp.find_existing_cluster(conn, opts, cluster_name)
print ("********Launching experiment at utilization %s with sample ratio %s..." %
(utilization, sample_ratio))
print ("********Deploying with arrival rate %s and warmup arrival rate %s"
% (arrival_rate_s, warmup_arrival_rate_s))
ec2_exp.deploy_cluster(frontends, backends, opts, warmup_arrival_rate_s, warmup_s,
post_warmup_s, nm_task_scheduler, users)
ec2_exp.start_sparrow(frontends, backends, opts)
print "*******Sleeping after starting Sparrow"
time.sleep(10)
print "********Starting prototype frontends and backends"
ec2_exp.start_proto(frontends, backends, opts)
time.sleep(trial_length)
log_dirname = "/disk1/sparrow/isolation_%s_%s" % (utilization, sample_ratio)
while os.path.exists(log_dirname):
log_dirname = "%s_a" % log_dirname
os.mkdir(log_dirname)
ec2_exp.execute_command(frontends, backends, opts, "./find_bugs.sh")
print "********Stopping prototypes and Sparrow"
ec2_exp.stop_proto(frontends, backends, opts)
ec2_exp.stop_sparrow(frontends, backends, opts)
print "********Collecting logs and placing in %s" % log_dirname
opts.log_dir = log_dirname
ec2_exp.collect_logs(frontends, backends, opts)
run_cmd("gunzip %s/*.gz" % log_dirname)
print "********Parsing logs"
run_cmd(("cd /tmp/sparrow/src/main/python/ && ./parse_logs.sh log_dir=%s "
"output_dir=%s/results start_sec=350 end_sec=450 && cd -") %
(log_dirname, log_dirname))
def main(argv):
launch_instances = False
if len(argv) >= 1 and argv[0] == "True":
launch_instances = True
utilizations = [1.0]
sample_ratios = [2.0]
sample_ratio_constrained = 1
# Amount of time it takes each task to run in isolation
task_duration_ms = 100
tasks_per_job = 3
private_ssh_key = "patkey.pem"
sparrow_branch = "debugging"
num_backends = 10
num_frontends = 1
cores_per_backend = 4
# Run each trial for many minutes.
trial_length = 700
num_preferred_nodes = 0
nm_task_scheduler = "round_robin"
full_utilization_rate_s = (float(num_backends * cores_per_backend * 1000) /
(task_duration_ms * tasks_per_job * num_frontends))
# Warmup information
warmup_s = 120
post_warmup_s = 30
warmup_arrival_rate_s = 0.4 * full_utilization_rate_s
if launch_instances:
print "********Launching instances..."
run_cmd("./ec2-exp.sh launch -f %s -b %s -i %s" %
(num_frontends, num_backends, private_ssh_key))
time.sleep(10)
for sample_ratio in sample_ratios:
for utilization in utilizations:
arrival_rate_s = utilization * full_utilization_rate_s
# This is a little bit of a hacky way to pass args to the ec2 script.
(opts, args) = ec2_exp.parse_args(False)
opts.identity_file = private_ssh_key
opts.arrival_rate = arrival_rate_s
opts.branch = sparrow_branch
opts.sample_ratio = sample_ratio
opts.sample_ratio_constrained = sample_ratio_constrained
opts.tasks_per_job = tasks_per_job
opts.num_preferred_nodes = num_preferred_nodes
opts.frontend_type = "FairnessTestingFrontend"
conn = boto.connect_ec2()
frontends, backends = ec2_exp.find_existing_cluster(conn, opts)
print ("********Launching experiment at utilization %s with sample ratio %s..." %
(utilization, sample_ratio))
print ("********Deploying with arrival rate %s and warmup arrival rate %s"
% (arrival_rate_s, warmup_arrival_rate_s))
ec2_exp.deploy_cluster(frontends, backends, opts, warmup_arrival_rate_s, warmup_s,
post_warmup_s, nm_task_scheduler)
ec2_exp.start_sparrow(frontends, backends, opts)
print "*******Sleeping after starting Sparrow"
time.sleep(10)
print "********Starting prototype frontends and backends"
ec2_exp.start_proto(frontends, backends, opts)
time.sleep(trial_length)
log_dirname = "/Users/keo/Documents/opportunistic-scheduling/sparrow/deploy/ec2/fairness_%s_%s" % (utilization, sample_ratio)
while os.path.exists(log_dirname):
log_dirname = "%s_a" % log_dirname
os.mkdir(log_dirname)
ec2_exp.execute_command(frontends, backends, opts, "./find_bugs.sh")
print "********Stopping prototypes and Sparrow"
ec2_exp.stop_proto(frontends, backends, opts)
ec2_exp.stop_sparrow(frontends, backends, opts)
print "********Collecting logs and placing in %s" % log_dirname
opts.log_dir = log_dirname
ec2_exp.collect_logs(frontends, backends, opts)
run_cmd("gunzip %s/*.gz" % log_dirname)
print "********Parsing logs"
run_cmd(("cd ../../src/main/python/ && ./parse_logs.sh log_dir=%s "
"output_dir=%s/results start_sec=240 end_sec=540 && cd -") %
(log_dirname, log_dirname))
def main(argv):
launch_instances = False
if len(argv) >= 1 and argv[0] == "True":
launch_instances = True
utilizations = [0.8, 0.9]
sample_ratios = [1, 1.1, 1.2, 1.5, 2.0, 3.0]
sample_ratio_constrained = 2
# Amount of time it takes each task to run in isolation
task_duration_ms = 100
tasks_per_job = 10
private_ssh_key = "patkey.pem"
sparrow_branch = "master"
nm_task_scheduler = "fifo"
num_backends = 100
num_frontends = 10
cores_per_backend = 8
# Run each trial for 5 minutes.
trial_length = 400
num_preferred_nodes = 0
num_users = 1
cluster = "probe"
full_utilization_rate_s = (
float(num_backends * cores_per_backend * 1000) /
(task_duration_ms * tasks_per_job * num_frontends))
# Warmup information
warmup_s = 30
post_warmup_s = 30
warmup_arrival_rate_s = 0.4 * full_utilization_rate_s
if launch_instances:
print "********Launching instances..."
run_cmd(
"./ec2-exp.sh launch %s -f %s -b %s -i %s" % # --spot-price %s" %
(cluster, num_frontends, num_backends, private_ssh_key))
time.sleep(10)
for sample_ratio in sample_ratios:
for utilization in utilizations:
arrival_rate_s = utilization * full_utilization_rate_s
# This is a little bit of a hacky way to pass args to the ec2 script.
(opts, args) = ec2_exp.parse_args(False)
opts.identity_file = private_ssh_key
opts.arrival_rate = arrival_rate_s
opts.branch = sparrow_branch
opts.sample_ratio = sample_ratio
opts.sample_ratio_constrained = sample_ratio_constrained
opts.tasks_per_job = tasks_per_job
opts.num_preferred_nodes = num_preferred_nodes
opts.cpus = cores_per_backend
conn = boto.connect_ec2()
frontends, backends = ec2_exp.find_existing_cluster(
conn, opts, cluster)
print(
"********Launching experiment at utilization %s with sample ratio %s..."
% (utilization, sample_ratio))
print(
"********Deploying with arrival rate %s and warmup arrival rate %s"
% (arrival_rate_s, warmup_arrival_rate_s))
ec2_exp.deploy_cluster(frontends, backends, opts,
warmup_arrival_rate_s, warmup_s,
post_warmup_s, nm_task_scheduler)
ec2_exp.start_sparrow(frontends, backends, opts)
print "*******Sleeping after starting Sparrow"
time.sleep(10)
print "********Starting prototype frontends and backends"
ec2_exp.start_proto(frontends, backends, opts)
time.sleep(trial_length)
log_dirname = "/home/ec2-user/sparrow/deploy/ec2/probe_ratio_%s_%s" % (
utilization, sample_ratio)
while os.path.exists(log_dirname):
log_dirname = "%s_a" % log_dirname
os.mkdir(log_dirname)
ec2_exp.execute_command(frontends, backends, opts,
"./find_bugs.sh")
print "********Stopping prototypes and Sparrow"
ec2_exp.stop_proto(frontends, backends, opts)
ec2_exp.stop_sparrow(frontends, backends, opts)
print "********Collecting logs and placing in %s" % log_dirname
opts.log_dir = log_dirname
ec2_exp.collect_logs(frontends, backends, opts)
def main(argv):
launch_instances = False
if len(argv) >= 1 and argv[0] == "True":
launch_instances = True
utilization_user_pairs = [(0.25, "high:1:0"), (0.5, "high:1:0,low:1:0"),
(0.75, "high:1:0,low:2:0"),
(1.0, "high:1:0,low:3:0"),
(1.25, "high:1:0,low:4:0"),
(1.5, "high:1:0,low:5:0"),
(1.75, "high:1:0,low:6:0"),
(2.0, "high:1:0,low:7:0")]
sample_ratios = [2.0]
sample_ratio_constrained = 1
# Amount of time it takes each task to run in isolation
task_duration_ms = 100
tasks_per_job = 1
private_ssh_key = "patkey.pem"
sparrow_branch = "debugging"
num_backends = 5
num_frontends = 1
cores_per_backend = 4
# Run each trial for 5 minutes.
trial_length = 500
num_preferred_nodes = 0
nm_task_scheduler = "priority"
cluster_name = "isolation"
full_utilization_rate_s = (
float(num_backends * cores_per_backend * 1000) /
(task_duration_ms * tasks_per_job * num_frontends))
# Warmup information
warmup_s = 120
post_warmup_s = 30
warmup_arrival_rate_s = 0.4 * full_utilization_rate_s
if launch_instances:
print "********Launching instances..."
run_cmd(
("./ec2-exp.sh launch %s --ami ami-a658c0cf " +
"--instance-type cr1.8xlarge --spot-price %s -f %s -b %s -i %s") %
(cluster_name, 0.5, num_frontends, num_backends, private_ssh_key))
time.sleep(10)
for sample_ratio in sample_ratios:
for utilization, users in utilization_user_pairs:
arrival_rate_s = utilization * full_utilization_rate_s
# This is a little bit of a hacky way to pass args to the ec2 script.
(opts, args) = ec2_exp.parse_args(False)
opts.identity_file = private_ssh_key
opts.arrival_rate = arrival_rate_s
opts.branch = sparrow_branch
opts.sample_ratio = sample_ratio
opts.sample_ratio_constrained = sample_ratio_constrained
opts.tasks_per_job = tasks_per_job
opts.num_preferred_nodes = num_preferred_nodes
opts.cpus = cores_per_backend
conn = boto.connect_ec2()
frontends, backends = ec2_exp.find_existing_cluster(
conn, opts, cluster_name)
print(
"********Launching experiment at utilization %s with sample ratio %s..."
% (utilization, sample_ratio))
print(
"********Deploying with arrival rate %s and warmup arrival rate %s"
% (arrival_rate_s, warmup_arrival_rate_s))
ec2_exp.deploy_cluster(frontends, backends, opts,
warmup_arrival_rate_s, warmup_s,
post_warmup_s, nm_task_scheduler, users)
ec2_exp.start_sparrow(frontends, backends, opts)
print "*******Sleeping after starting Sparrow"
time.sleep(10)
print "********Starting prototype frontends and backends"
ec2_exp.start_proto(frontends, backends, opts)
time.sleep(trial_length)
log_dirname = "/disk1/sparrow/isolation_%s_%s" % (utilization,
sample_ratio)
while os.path.exists(log_dirname):
log_dirname = "%s_a" % log_dirname
os.mkdir(log_dirname)
ec2_exp.execute_command(frontends, backends, opts,
"./find_bugs.sh")
print "********Stopping prototypes and Sparrow"
ec2_exp.stop_proto(frontends, backends, opts)
ec2_exp.stop_sparrow(frontends, backends, opts)
print "********Collecting logs and placing in %s" % log_dirname
opts.log_dir = log_dirname
ec2_exp.collect_logs(frontends, backends, opts)
run_cmd("gunzip %s/*.gz" % log_dirname)
print "********Parsing logs"
run_cmd((
"cd /tmp/sparrow/src/main/python/ && ./parse_logs.sh log_dir=%s "
"output_dir=%s/results start_sec=350 end_sec=450 && cd -") %
(log_dirname, log_dirname))