Add support to specify multiple partitions as 'setonix/*'

    python multi-part-sim.py -x setonix/part-cpu setonix/part-gpu

or simply:

    python multi-part-sim.py -x setonix/*

This will simulate synthetic workloads on two partitions as defined in `config/setonix-cpu` and `config/setonix-gpu`. To replay telemetry workloads from another system, e.g., Marconi100's PM100 dataset, first create a .npz snapshot of the telemetry data, e.g., 

    python main.py --system marconi100 -f /path/to/marconi100/job_table.parquet

This will dump a .npz file with a randomized name, e.g. ac23db.npz. Let's rename this file to pm100.npz for clarity. Note: can control-C when the simulation starts. Now, this pm100.npz file can be used with `multi-part-sim.py` as follows:

    python multi-part-sim.py -x setonix/part-cpu setonix/part-gpu -f pm100.npz --reschedule --scale 192

    python multi-part-sim.py -x setonix/* -f pm100.npz --reschedule --scale 192

The `--reschedule` flag will use the internal scheduler to determine what nodes to schedule for each job, and the `--scale` flag will specify the maximum number of nodes for each job (generally set this to the max number of nodes of the smallest partition). 

from raps.helpers import check_python_version

check_python_version()

import glob

import os

import random

import sys

from args import args

from raps.config import ConfigManager

from raps.config import ConfigManager, CONFIG_PATH

from raps.policy import PolicyType

from raps.ui import LayoutManager

from raps.scheduler import Scheduler

# Load configurations for each partition

partition_names = args.partitions

print(args.partitions)

if '*' in args.partitions[0]:

    paths = glob.glob(os.path.join(CONFIG_PATH, args.partitions[0]))

    partition_names = [os.path.join(*p.split(os.sep)[-2:]) for p in paths]

configs = [ConfigManager(system_name=partition).get_config() for partition in partition_names]

args_dicts = [{**vars(args), 'config': config} for config in configs]