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#! /usr/bin/env python3
# Copyright (c) 2006-2025. The SimGrid Team. All rights reserved.
# This program is free software; you can redistribute it and/or modify it
# under the terms of the license (GNU LGPL) which comes with this package.
# This script takes as input a C++ platform file, compiles it, then dumps the
# routing graph as a CSV and generates an image.
# The layout should be alright for any platform file, but the colors are very
# ad-hoc for file supernode.cpp : do not hesitate to adapt this script to your needs.
# An option is provided to "simplify" the graph by removing the link vertices. It assumes that these vertices have
# "link" in their name.
import sys
import subprocess
import pandas
import matplotlib.pyplot as plt
import networkx as nx
import argparse
import tempfile
import os
try:
from palettable.colorbrewer.qualitative import Set1_9
colors = Set1_9.hex_colors
except ImportError:
print('Warning: could not import palettable, will use a default palette.')
colors = [None]*10
def run_command(cmd):
print(cmd)
proc = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE)
_stdout, stderr = proc.communicate()
if proc.returncode != 0:
sys.exit(f'Command failed:\n{stderr.decode()}')
def compile_platform(platform_cpp, platform_so):
cmd = f'g++ -g -fPIC -shared -o {platform_so} {platform_cpp} -lsimgrid'
run_command(cmd)
def dump_csv(platform_so, platform_csv):
cmd = f'graphicator {platform_so} {platform_csv}'
run_command(cmd)
def merge_updown(graph):
'''
Merge all the UP and DOWN links.
'''
graph2 = graph.copy()
downlinks = [v for v in graph if 'DOWN' in v]
mapping = {}
for down in downlinks:
up = down.replace('DOWN', 'UP')
graph2 = nx.contracted_nodes(graph2, down, up)
mapping[down] = down.replace('_DOWN', '')
return nx.relabel_nodes(graph2, mapping)
def contract_links(graph):
'''
Remove all the 'link' vertices from the graph to directly connect the nodes.
Note: it assumes that link vertices have the "link" string in their name.
'''
links = [v for v in graph if 'link' in v]
new_edges = []
for v in links:
neigh = [u for u in graph.neighbors(v) if 'link' not in u] # with Floyd zones, we have links connected to links
assert len(neigh) == 2
new_edges.append(neigh)
# Adding edges from graph that have no links
for u, v in graph.edges:
if 'link' not in u and 'link' not in v:
new_edges.append((u, v))
return nx.from_edgelist(new_edges)
def load_graph(platform_csv, simplify_graph):
edges = pandas.read_csv(platform_csv)
graph = nx.Graph()
graph.add_edges_from([e for _, e in edges.drop_duplicates().iterrows()])
print(f'Loaded a graph with {len(graph)} vertices with {len(graph.edges)} edges')
if simplify_graph:
graph = contract_links(merge_updown(graph))
print(f'Simplified the graph, it now has {len(graph)} vertices with {len(graph.edges)} edges')
return graph
def plot_graph(graph, label=False, groups=None):
if groups is None:
groups = []
# First, we compute the graph layout, i.e. the position of the nodes.
# The neato algorithm from graphviz is nicer, but this is an extra-dependency.
# The spring_layout is also not too bad.
try:
pos = nx.nx_agraph.graphviz_layout(graph, 'neato')
except ImportError:
print('Warning: could not import pygraphviz, will use another layout algorithm.')
pos = nx.spring_layout(graph, k=0.5, iterations=1000, seed=42)
plt.figure(figsize=(20, 15))
plt.axis('off')
all_nodes = set(graph)
# We then iterate on all the specified groups, to plot each of them in the right color.
# Note that the order of the groups is important here, as we are looking at substrings in the node names.
for i, grp in enumerate(groups):
nodes = {u for u in all_nodes if grp in u}
all_nodes -= nodes
nx.draw_networkx_nodes(graph, pos, nodelist=nodes, node_size=50, node_color=colors[i], label=grp.replace('_', ''))
nx.draw_networkx_nodes(graph, pos, nodelist=all_nodes, node_size=50, node_color=colors[-1], label='unknown')
# Finally we draw the edges, the (optional) labels, and the legend.
nx.draw_networkx_edges(graph, pos, alpha=0.3)
if label:
nx.draw_networkx_labels(graph, pos)
plt.legend(scatterpoints=1)
def generate_svg(platform_csv, output_file, simplify_graph):
graph = load_graph(platform_csv, simplify_graph)
plot_graph(graph, label=False, groups=['router', 'link', 'cpu', '_node', 'supernode', 'cluster'])
plt.savefig(output_file)
print(f'Generated file {output_file}')
def main():
parser = argparse.ArgumentParser(description='Visualization of topologies for SimGrid C++ platforms')
parser.add_argument('input', type=str, help='SimGrid C++ platform file name (input)')
parser.add_argument('output', type=str, help='File name of the output image')
parser.add_argument('--simplify', action='store_true', help='Simplify the topology (removing link vertices)')
args = parser.parse_args()
if not args.input.endswith('.cpp'):
parser.error(f'SimGrid platform must be a C++ file (with .cpp extension), got {args.input}')
if not os.path.isfile(args.input):
parser.error(f'File {args.input} not found')
output_dir = os.path.dirname(args.output)
if output_dir != '' and not os.path.isdir(output_dir):
parser.error(f'Not a directory: {output_dir}')
with tempfile.TemporaryDirectory() as tmpdirname:
platform_cpp = args.input
platform_csv = os.path.join(tmpdirname, 'platform.csv')
platform_so = os.path.join(tmpdirname, 'platform.so')
compile_platform(platform_cpp, platform_so)
dump_csv(platform_so, platform_csv)
generate_svg(platform_csv, args.output, args.simplify)
if __name__ == '__main__':
main()
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