script: compute max observed watts & instance gen

scripts-py/expe_energumen/m100_find_max_power.py

+#!/usr/bin/env python3
+import argparse
+import os
+import pandas as pd
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("input_power_timeseries_prefix", help="filepath prefix to the location of the parquet files that contain node power consumption time series")
+    parser.add_argument("month", nargs='+', help="the month to aggregate. example value: '22-07'")
+    args = parser.parse_args()
+
+    overall_max = -1
+    for month in args.month:
+        month_prefix = f'{args.input_power_timeseries_prefix}{month}'
+        power_file = f'{month_prefix}_power_total.parquet'
+
+        df = pd.read_parquet(power_file)
+        max_month_power = df.groupby('timestamp')['value'].sum().max()
+        print(f'max power reached during month {month}: {max_month_power} W')
+        overall_max = max(overall_max, max_month_power)
+    print(f'max power reached over all months: {overall_max} W')

scripts-py/expe_energumen/m100_generate_expe_params.py

+#!/usr/bin/env python3
+import argparse
+import itertools
+import json
+import sys
+from functools import reduce
+from hashlib import sha1
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("workload_params", type=str, help='path to the workload params JSON file')
+    parser.add_argument("-o", "--output_file", type=str, help="if set, write output to this file instead of stdout")
+    args = parser.parse_args()
+
+    max_observed_total_power = 955080
+    max_power_per_node = 2100.0
+    min_power_per_node = 240.0
+    nb_nodes = 980
+    max_dynamic_power = max_observed_total_power - min_power_per_node * nb_nodes
+    powercaps = [{
+        'powercap_dynamic_value_ratio': f'{i * 0.1:.1f}',
+        'powercap_dynamic_watts': int(i * 0.1 * max_dynamic_power),
+        'normal_dynamic_watts': max_dynamic_power,
+        'idle_watts': nb_nodes * min_power_per_node,
+    } for i in range(2,11,2)]
+
+    powercap_durations = [
+        {'powercap_end_time_seconds': 60*60*3},
+    ]
+
+    algo_name = 'easypower'
+    predictors = [
+        {'algo_name': algo_name, 'predictor_name': 'zero', 'job_power_estimation_field': 'zero_power_estimation'},
+        {'algo_name': algo_name, 'predictor_name': 'mean', 'job_power_estimation_field': 'mean_power_estimation'},
+        {'algo_name': algo_name, 'predictor_name': 'max', 'job_power_estimation_field': 'max_power_estimation'},
+        {'algo_name': algo_name, 'predictor_name': 'upper_bound', 'job_power_estimation_field': 'upper_bound_power_estimation'},
+        {'algo_name': algo_name, 'predictor_name': 'real_mean', 'job_power_estimation_field': 'real_mean_power_estimation'},
+        {'algo_name': algo_name, 'predictor_name': 'real_max', 'job_power_estimation_field': 'real_max_power_estimation'},
+    ]
+
+    with open(args.workload_params) as wf:
+        wl_params = json.load(wf)
+
+    nb_instances = 0
+    instances = dict()
+    for instance_t in itertools.product(predictors, powercaps, powercap_durations, wl_params):
+        instance = reduce(lambda a,b: {**a, **b}, instance_t)
+        encoded_without_hash = json.dumps(instance, sort_keys=True).encode('utf-8')
+        instance_hash = sha1(encoded_without_hash).hexdigest()
+        instances[instance_hash] = instance
+        nb_instances += 1
+    assert nb_instances == len(instances), 'collision: two instances have the same hash'
+
+    f = sys.stdout
+    if args.output_file is not None:
+        f = open(args.output_file, 'w')
+    print(json.dumps(instances, sort_keys=True), file=f)

scripts-py/pyproject.toml

@@ -19,3 +19,5 @@ m100-generate-batsim-workload = "expe_energumen.m100_generate_batsim_workload:ma
 m100-compute-gantt-power-consumption = "expe_energumen.m100_compute_gantt_power_consumption:main"
 m100-generate-expe-workload-params = "expe_energumen.m100_generate_expe_workload_params:main"
 m100-generate-expe-workloads = "expe_energumen.m100_generate_expe_workloads:main"
+m100-generate-expe-params = "expe_energumen.m100_generate_expe_params:main"
+m100-find-max-power = "expe_energumen.m100_find_max_power:main"