From 1aee0e38f3cea09bac0d39d03c2b63989094825f Mon Sep 17 00:00:00 2001
From: Simon Bjurek <simbj106@student.liu.se>
Date: Tue, 8 Apr 2025 15:24:16 +0200
Subject: [PATCH] Add pre-coloring of largest clique to ILP algorithms for
better performance
---
b_asic/resources.py | 16 +++++++++++++---
1 file changed, 13 insertions(+), 3 deletions(-)
diff --git a/b_asic/resources.py b/b_asic/resources.py
index 1b5f93fb..058e9419 100644
--- a/b_asic/resources.py
+++ b/b_asic/resources.py
@@ -1445,7 +1445,7 @@ class ProcessCollection:
# 1 - nodes have exactly one color
# 2 - adjacent nodes cannot have the same color
# 3 - only permit assignments if color is used
- # 4 - reduce solution space by setting the color of one node
+ # 4 - reduce solution space by assigning colors to the largest clique
for node in nodes:
problem += lpSum(x[node][i] for i in colors) == 1
for u, v in edges:
@@ -1454,7 +1454,9 @@ class ProcessCollection:
for node in nodes:
for color in colors:
problem += x[node][color] <= c[color]
- problem += x[nodes[0]][0] == c[0] == 1
+ max_clique = next(nx.find_cliques(exclusion_graph))
+ for color, node in enumerate(max_clique):
+ problem += x[node][color] == c[color] == 1
status = problem.solve()
@@ -1521,7 +1523,8 @@ class ProcessCollection:
# 1 - nodes have exactly one color
# 2 - adjacent nodes cannot have the same color
# 3 - only permit assignments if color is used
- # 4 - if node is colored then enable the PE which generates that node (variable)
+ # 4 - if node is colored then enable the PE which generates that node
+ # 5 - reduce solution space by assigning colors to the largest clique
for node in nodes:
problem += lpSum(x[node][i] for i in colors) == 1
for u, v in edges:
@@ -1534,6 +1537,9 @@ class ProcessCollection:
pe = _get_source(node, processing_elements)
for color in colors:
problem += x[node][color] <= y[pe][color]
+ max_clique = next(nx.find_cliques(exclusion_graph))
+ for color, node in enumerate(max_clique):
+ problem += x[node][color] == c[color] == 1
status = problem.solve()
@@ -1601,6 +1607,7 @@ class ProcessCollection:
# 2 - adjacent nodes cannot have the same color
# 3 - only permit assignments if color is used
# 4 - if node is colored then enable the PE reads from that node (variable)
+ # 5 - reduce solution space by assigning colors to the largest clique
for node in nodes:
problem += lpSum(x[node][i] for i in colors) == 1
for u, v in edges:
@@ -1613,6 +1620,9 @@ class ProcessCollection:
pe = _get_destination(node, processing_elements)
for color in colors:
problem += x[node][color] <= y[pe][color]
+ max_clique = next(nx.find_cliques(exclusion_graph))
+ for color, node in enumerate(max_clique):
+ problem += x[node][color] == c[color] == 1
status = problem.solve()
--
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