Add scripts for the paper

Author: adityapb

examples/v2beta1/charm/generate_jobs.py

@@ -14,7 +14,7 @@
 njobs = 16
 
 
-def create_job(prefix, job_index, priority, problem_size, min_replicas, max_replicas, timesteps):
+def create_job(mode, prefix, job_index, priority, problem_size, min_replicas, max_replicas, timesteps):
     with open("charm-template.yaml", "r") as file:
         template = file.read()
 
@@ -23,22 +23,30 @@ def create_job(prefix, job_index, priority, problem_size, min_replicas, max_repl
     num_chares = 2 ** (num_chares - 1).bit_length()
     chare_size = problem_size // num_chares
 
+    if mode == "min":
+        max_replicas = min(min_replicas - 1, 59)
+    elif mode == "max":
+        min_replicas = min(max_replicas - 1, 59)
+    elif mode == "elastic" or mode == "moldable":
+        min_replicas = min(min_replicas - 1, 59)
+        max_replicas = min(max_replicas - 1, 59)
+
     job_yaml = template.format(
         prefix=prefix,
         job_index=job_index,
         priority=priority,
         problem_size=problem_size,
         chare_size=chare_size,
         timesteps=timesteps,
-        min_replicas=min(max_replicas-1, 59),
-        max_replicas=min(max_replicas-1, 59),
+        min_replicas=min_replicas,
+        max_replicas=max_replicas,
     )
 
-    with open(f"jobs_elastic/charm-job-{job_index}.yaml", "w") as file:
+    with open(f"jobs_{mode}/charm-job-{job_index}.yaml", "w") as file:
         file.write(job_yaml)
 
 
-def generate_jobs():
+def generate_jobs(mode):
     sizes_per_pe = [256, 512, 1024, 1024]
     min_pes = [2, 4, 8, 16]
     timesteps_per_job = [40000, 40000, 40000, 10000]
@@ -57,12 +65,12 @@ def generate_jobs():
         problem_size = min_replicas * sizes_per_pe[idx]
         timesteps = timesteps_per_job[idx]
         prefix = job_prefixes[idx]
-        create_job(prefix, i, priority, problem_size, min_replicas, max_replicas, timesteps)
+        create_job(mode, prefix, i, priority, problem_size, min_replicas, max_replicas, timesteps)
 
 
-def submit_jobs():
+def submit_jobs(mode):
     for job_index in range(njobs):
-        job_file = f"jobs_elastic/charm-job-{job_index}.yaml"
+        job_file = f"jobs_{mode}/charm-job-{job_index}.yaml"
         print(f"Submitting {job_file}")
         # Here you would submit the job using your cluster's job submission command
         os.system(f"kubectl apply -f {job_file}")
@@ -72,10 +80,11 @@ def submit_jobs():
 
 
 if __name__ == "__main__":
-    if sys.argv[1] == "generate_jobs":
-        generate_jobs()
+    mode = sys.argv[2]
+    if sys.argv[1] == "generate":
+        generate_jobs(mode)
     elif sys.argv[1] == "submit":
-        submit_jobs()
+        submit_jobs(mode)
     else:
         print("Invalid argument. Use 'generate_jobs' to generate job files or 'submit' to submit them.")
         sys.exit(1)

examples/v2beta1/charm/simulation/run.py

@@ -116,7 +116,6 @@ def generate_job_list(nexps):
         jobs_list = []
         for i in range(njobs):
             idx = choice(indices)
-            #priority = (3 - idx) + randint(1, 2)
             priority = randint(1, 5)
             min_replicas = min_pes[idx] - 1
             max_replicas = min(4 * (min_replicas + 1), 60) - 1
@@ -417,24 +416,18 @@ def find_critical_experiment(modes, max_pes):
     job_prefixes = ["small", "medium", "large", "xlarge"]
     counts = [0, 0, 0, 0]
     njobs = 16
-    #njobs = 9
 
-    #jobs = [2, 3, 2, 1, 0, 1, 1, 1, 0, 1, 1, 2, 0, 1, 1, 1]
-    #priorities = [2, 1, 3, 3, 4, 3, 3, 3, 5, 3, 3, 2, 4, 3, 3, 3]
     jobs = [2, 1, 1, 0, 3, 3, 0, 3, 1, 1, 0, 3, 0, 1, 1, 1]
     priorities = [2, 3, 4, 4, 2, 1, 4, 1, 4, 3, 4, 1, 5, 3, 3, 3]
-    #jobs = [2, 3, 2, 1, 0, 1, 1, 1, 0]
 
     jobs_list = []
     for i, job_index in enumerate(jobs):
         idx = job_index
-        #priority = (3 - job_index) + randint(1, 2)
-        #print(priority)
         priority = priorities[i]
         min_replicas = min_pes[idx] - 1
         max_replicas = min(4 * (1 + min_replicas), 60) - 1
         problem_size = (min_replicas + 1) * sizes_per_pe[idx]
-        timesteps = timesteps_per_job[idx] #+ 100 * randint(0, 10)
+        timesteps = timesteps_per_job[idx]
         prefix = job_prefixes[idx]
         #create_job(prefix, i, priority, problem_size, min_replicas, max_replicas, timesteps)
 
@@ -453,6 +446,6 @@ def find_critical_experiment(modes, max_pes):
     #plot_utilization(events, jobs, 60)
     #print(events)
     #print(get_stats(events, 60))
-    #vary_rescale_gap(["elastic", "moldable", "min_replicas", "max_replicas"], 60)
-    #vary_submission_time(["elastic", "moldable", "min_replicas", "max_replicas"], 60)
+    vary_rescale_gap(["elastic", "moldable", "min_replicas", "max_replicas"], 60)
+    vary_submission_time(["elastic", "moldable", "min_replicas", "max_replicas"], 60)
     #find_critical_experiment(["elastic", "moldable", "min_replicas", "max_replicas"], 60)

examples/v2beta1/charm/track_utilization.py

@@ -1,7 +1,10 @@
 import subprocess
 import time
+import sys
 
-output_file = "/home/aditya/mpi-operator/examples/v2beta1/charm/pod_utilization_moldable_new.log"
+mode = sys.argv[1]
+
+output_file = f"pod_utilization_{mode}.log"
 
 open(output_file, "w").close()  # Clear the file before starting