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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import subprocess
import re
import sys
import argparse
from rich.console import Console
from rich.table import Table
from rich import box
# ---------------------- USAGE GUIDE ----------------------
# This script fetches and displays the GPU, CPU, and memory usage
# per user for each Quality of Service (QOS) associated with a given account.
# It shows the resources used in active jobs for each QOS and the
# total allowable resources for each QOS.
#
# Usage:
# python script.py --account <account_name>
#
# Example:
# python script.py --account cortex
# ---------------------------------------------------------
# Initialize the console
console = Console()
# Setup argparse to handle account as command-line argument (no QOS argument)
parser = argparse.ArgumentParser(description='Fetch resource usage from SLURM.')
parser.add_argument('--account', type=str, required=True, help='Account name for SLURM query')
args = parser.parse_args()
account_name = args.account
# Function to extract available QOS for the account using the pipe-separated format
def get_qos_for_account(account):
sacctmgr_qos_command = (
f"sacctmgr show assoc format=Account,User,QOS where Account={account} -P"
)
# Run the command and capture stdout and stderr
result_qos = subprocess.run(sacctmgr_qos_command, shell=True, capture_output=True, text=True)
output = result_qos.stdout.strip()
# Extract the QOS column (3rd column) from the pipe-separated output
qos_set = set() # Use a set to avoid duplicates
for line in output.splitlines()[1:]: # Skip the header
fields = line.split("|")
if len(fields) == 3 and fields[2].strip(): # Ensure we have 3 fields and QOS is not empty
# QOS can have multiple values, split them by commas
qos_values = fields[2].split(",")
for qos in qos_values:
qos_set.add(qos.strip()) # Strip any whitespace
# Ensure that "lowest" QOS comes first, if present
qos_list = sorted(qos_set, key=lambda x: (x != 'lowest', x))
return qos_list
# Fetch QOS values associated with the account
qos_list = get_qos_for_account(account_name)
# Check if we found any QOS values
if not qos_list:
console.print(f"[red]No QOS found for account {account_name}[/red]")
sys.exit(1)
# Function to extract CPU, GPU, and memory usage from the ReqTRES or AllocTRES column
def extract_tres_usage(tres_str):
cpu_usage = gpu_usage = memory_usage = 0
if 'cpu=' in tres_str:
cpu_match = re.search(r'cpu=([0-9]+)', tres_str)
cpu_usage = int(cpu_match.group(1)) if cpu_match else 0
if 'gres/gpu=' in tres_str:
gpu_match = re.search(r'gres/gpu=([0-9]+)', tres_str)
gpu_usage = int(gpu_match.group(1)) if gpu_match else 0
if 'mem=' in tres_str:
mem_match = re.search(r'mem=([0-9]+)([A-Za-z]+)', tres_str)
if mem_match:
mem_value, mem_unit = int(mem_match.group(1)), mem_match.group(2)
# Convert memory to GB for consistent reporting
memory_usage = mem_value if mem_unit == 'G' else mem_value / 1024 if mem_unit == 'M' else mem_value * 1024
return cpu_usage, memory_usage, gpu_usage
# Loop through each QOS for the account
for qos_name in qos_list:
console.print(f"\n[bold green]Fetching data for QOS: {qos_name}[/bold green]\n")
# Construct the sacctmgr command to get total allowable resources for the QOS
sacctmgr_command = [
"sacctmgr",
"show",
"qos",
qos_name,
"format=GrpTRES%50",
"-P"
]
# Fetch total allowable resources for the QOS
result_qos_resources = subprocess.run(sacctmgr_command, capture_output=True, text=True)
qos_output = result_qos_resources.stdout.strip()
# Extract the CPU, GPU, and memory limits from GrpTRES
cpu_limit = gpu_limit = memory_limit = "N/A"
cpu_match = re.search(r'cpu=([0-9]+)', qos_output)
gpu_match = re.search(r'gres/gpu=([0-9]+)', qos_output)
mem_match = re.search(r'mem=([0-9]+)([A-Za-z]+)', qos_output)
if cpu_match:
cpu_limit = int(cpu_match.group(1))
if gpu_match:
gpu_limit = int(gpu_match.group(1))
if mem_match:
mem_value, mem_unit = int(mem_match.group(1)), mem_match.group(2)
# Convert memory to GB
memory_limit = mem_value if mem_unit == 'G' else mem_value / 1024 if mem_unit == 'M' else mem_value * 1024
# Fetch job information for the given account and QOS
sacct_command = [
"sacct",
"-a",
"--qos=" + qos_name,
"--account=" + account_name,
"--format=JobID,User%20,Partition,JobName,State,ReqTRES%60,AllocTRES%60",
"-P"
]
result_jobs = subprocess.run(sacct_command, capture_output=True, text=True)
job_output = result_jobs.stdout.strip()
# Split the output into lines
job_lines = job_output.splitlines()
# Split the first row as the header
header = job_lines[0].split("|")
# Parse the output rows into a list of dictionaries
job_data = []
for line in job_lines[1:]:
fields = line.split("|")
if len(fields) == len(header):
job_data.append(dict(zip(header, fields)))
# Collect CPU, GPU, and memory usage per user for RUNNING jobs only, using ReqTRES for memory
cpu_usage_per_user = {}
mem_usage_per_user = {}
gpu_usage_per_user = {}
grand_total_cpu_usage = 0
grand_total_mem_usage = 0
grand_total_gpu_usage = 0
for job in job_data:
job_id = job['JobID']
user = job['User'].strip()
state = job['State'].strip()
# Only consider master jobs (JobID without dots), non-empty users, and RUNNING jobs
if '.' not in job_id and user and state == 'RUNNING':
# Use ReqTRES for memory usage since AllocTRES doesn't show it
cpu_usage, mem_usage, gpu_usage = extract_tres_usage(job['ReqTRES'])
if user not in cpu_usage_per_user:
cpu_usage_per_user[user] = 0
mem_usage_per_user[user] = 0
gpu_usage_per_user[user] = 0
cpu_usage_per_user[user] += cpu_usage
mem_usage_per_user[user] += int(mem_usage) # rounding memory usage to integer
gpu_usage_per_user[user] += gpu_usage
grand_total_cpu_usage += cpu_usage
grand_total_mem_usage += int(mem_usage)
grand_total_gpu_usage += gpu_usage
# Create a table using rich (without a divider)
table = Table(title=f"Resource Usage Summary per User (QOS: {qos_name})", box=box.SQUARE)
# Add columns to the table (GPU moved after user)
table.add_column("User", justify="left", style="cyan", no_wrap=True)
table.add_column("Total GPU Usage", justify="right", style="magenta")
table.add_column("Total CPU Usage", justify="right", style="magenta")
table.add_column("Total Memory Usage (GB)", justify="right", style="magenta")
# Add rows for each user with commas for readability
for user in cpu_usage_per_user:
table.add_row(
user,
f"{gpu_usage_per_user[user]:,}",
f"{cpu_usage_per_user[user]:,}",
f"{mem_usage_per_user[user]:,}"
)
# Add rows for the grand total
table.add_row("Grand Total", f"{grand_total_gpu_usage:,}", f"{grand_total_cpu_usage:,}", f"{grand_total_mem_usage:,}", style="bold")
# Format the total allowable resources and add to the table
formatted_cpu_limit = f"{cpu_limit:,}" if cpu_limit != "N/A" else cpu_limit
formatted_gpu_limit = f"{gpu_limit:,}" if gpu_limit != "N/A" else gpu_limit
formatted_mem_limit = f"{int(memory_limit):,}" if memory_limit != "N/A" else memory_limit
# Add a row for the total allowable resources for the specific QOS
table.add_row(f"Total Allowable Resources (QOS: {qos_name})", formatted_gpu_limit, formatted_cpu_limit, formatted_mem_limit, style="bold cyan")
# Display the table for the current QOS
console.print(table)
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