From 319637c07e0284d3aa83583c42e0a04d6fe4c4d7 Mon Sep 17 00:00:00 2001
From: Simon Bjurek <simbj106@student.liu.se>
Date: Tue, 8 Apr 2025 16:44:51 +0200
Subject: [PATCH] Add reduction of solution space by ignoring symmetry for ILP
resource algorithms
---
b_asic/resources.py | 46 +++++++++++++++++++++++++++++++--------------
1 file changed, 32 insertions(+), 14 deletions(-)
diff --git a/b_asic/resources.py b/b_asic/resources.py
index 058e9419..9771c040 100644
--- a/b_asic/resources.py
+++ b/b_asic/resources.py
@@ -1442,10 +1442,12 @@ class ProcessCollection:
problem += lpSum(c[i] for i in colors)
# constraints:
- # 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 assigning colors to the largest clique
+ # (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 assigning colors to the largest clique
+ # (5 & 6) - reduce solution space by ignoring the symmetry caused
+ # by cycling the graph colors
for node in nodes:
problem += lpSum(x[node][i] for i in colors) == 1
for u, v in edges:
@@ -1457,6 +1459,10 @@ class ProcessCollection:
max_clique = next(nx.find_cliques(exclusion_graph))
for color, node in enumerate(max_clique):
problem += x[node][color] == c[color] == 1
+ for color in colors:
+ problem += c[color] <= lpSum(x[node][color] for node in nodes)
+ for color in colors[:-1]:
+ problem += c[color + 1] <= c[color]
status = problem.solve()
@@ -1520,11 +1526,13 @@ class ProcessCollection:
problem += lpSum(y[pe][i] for pe in processing_elements for i in colors)
# constraints:
- # 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
- # 5 - reduce solution space by assigning colors to the largest clique
+ # (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
+ # (5) - reduce solution space by assigning colors to the largest clique
+ # (6 & 7) - reduce solution space by ignoring the symmetry caused
+ # by cycling the graph colors
for node in nodes:
problem += lpSum(x[node][i] for i in colors) == 1
for u, v in edges:
@@ -1540,6 +1548,10 @@ class ProcessCollection:
max_clique = next(nx.find_cliques(exclusion_graph))
for color, node in enumerate(max_clique):
problem += x[node][color] == c[color] == 1
+ for color in colors:
+ problem += c[color] <= lpSum(x[node][color] for node in nodes)
+ for color in colors[:-1]:
+ problem += c[color + 1] <= c[color]
status = problem.solve()
@@ -1603,11 +1615,13 @@ class ProcessCollection:
problem += lpSum(y[pe][i] for pe in processing_elements for i in colors)
# constraints:
- # 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 reads from that node (variable)
- # 5 - reduce solution space by assigning colors to the largest clique
+ # (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 reads from that node (variable)
+ # (5) - reduce solution space by assigning colors to the largest clique
+ # (6 & 7) - reduce solution space by ignoring the symmetry caused
+ # by cycling the graph colors
for node in nodes:
problem += lpSum(x[node][i] for i in colors) == 1
for u, v in edges:
@@ -1623,6 +1637,10 @@ class ProcessCollection:
max_clique = next(nx.find_cliques(exclusion_graph))
for color, node in enumerate(max_clique):
problem += x[node][color] == c[color] == 1
+ for color in colors:
+ problem += c[color] <= lpSum(x[node][color] for node in nodes)
+ for color in colors[:-1]:
+ problem += c[color + 1] <= c[color]
status = problem.solve()
--
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