CS 374: Algorithms & Models of Computation, Fall 2015 3-Color, Circuit-SAT and SAT Lecture 24 December 1, 2015 Chandra & Manoj (UIUC) CS374 1 Fall 2015 1 / 57
Recap NP : languages that have non-deterministic polynomial time algorithms Chandra & Manoj (UIUC) CS374 2 Fall 2015 2 / 57
Recap NP : languages that have non-deterministic polynomial time algorithms A language L is NP-Complete iff L is in NP for every L ′ in NP , L ′ ≤ P L Chandra & Manoj (UIUC) CS374 2 Fall 2015 2 / 57
Recap NP : languages that have non-deterministic polynomial time algorithms A language L is NP-Complete iff L is in NP for every L ′ in NP , L ′ ≤ P L L is NP-Hard if for every L ′ in NP , L ′ ≤ P L . Chandra & Manoj (UIUC) CS374 2 Fall 2015 2 / 57
Recap NP : languages that have non-deterministic polynomial time algorithms A language L is NP-Complete iff L is in NP for every L ′ in NP , L ′ ≤ P L L is NP-Hard if for every L ′ in NP , L ′ ≤ P L . Theorem (Cook-Levin) SAT is NP-Complete . Chandra & Manoj (UIUC) CS374 2 Fall 2015 2 / 57
Pictorial View NP-Hard NP-C NP P Chandra & Manoj (UIUC) CS374 3 Fall 2015 3 / 57
P and NP Possible scenarios: P = NP . 1 P � = NP 2 Chandra & Manoj (UIUC) CS374 4 Fall 2015 4 / 57
P and NP Possible scenarios: P = NP . 1 P � = NP 2 Question: Suppose P � = NP . Is every problem in NP \ P also NP-Complete ? Chandra & Manoj (UIUC) CS374 4 Fall 2015 4 / 57
P and NP Possible scenarios: P = NP . 1 P � = NP 2 Question: Suppose P � = NP . Is every problem in NP \ P also NP-Complete ? Theorem (Ladner) If P � = NP then there is a problem/language X ∈ NP \ P such that X is not NP-Complete . Chandra & Manoj (UIUC) CS374 4 Fall 2015 4 / 57
Today NP-Completeness of three problems: 3 -Color Circuit SAT SAT (Cook-Levin Theorem) Important: understanding the problems and that they are hard. Proofs and reductions will be sketchy and mainly to give a flavor Chandra & Manoj (UIUC) CS374 5 Fall 2015 5 / 57
Part I NP-Completeness of Graph Coloring Chandra & Manoj (UIUC) CS374 6 Fall 2015 6 / 57
Graph Coloring Problem: Graph Coloring Instance: G = ( V , E ) : Undirected graph, integer k . Question: Can the vertices of the graph be colored using k colors so that vertices connected by an edge do not get the same color? Chandra & Manoj (UIUC) CS374 7 Fall 2015 7 / 57
Graph 3-Coloring Problem: 3 Coloring Instance: G = ( V , E ) : Undirected graph. Question: Can the vertices of the graph be colored using 3 colors so that vertices connected by an edge do not get the same color? Chandra & Manoj (UIUC) CS374 8 Fall 2015 8 / 57
Graph 3-Coloring Problem: 3 Coloring Instance: G = ( V , E ) : Undirected graph. Question: Can the vertices of the graph be colored using 3 colors so that vertices connected by an edge do not get the same color? Chandra & Manoj (UIUC) CS374 8 Fall 2015 8 / 57
Graph Coloring Observation: If G is colored with k colors then each color class (nodes of same color) form an independent set in G . Thus, G can be partitioned into k independent sets iff G is k -colorable. Chandra & Manoj (UIUC) CS374 9 Fall 2015 9 / 57
Graph Coloring Observation: If G is colored with k colors then each color class (nodes of same color) form an independent set in G . Thus, G can be partitioned into k independent sets iff G is k -colorable. Graph 2 -Coloring can be decided in polynomial time. Chandra & Manoj (UIUC) CS374 9 Fall 2015 9 / 57
Graph Coloring Observation: If G is colored with k colors then each color class (nodes of same color) form an independent set in G . Thus, G can be partitioned into k independent sets iff G is k -colorable. Graph 2 -Coloring can be decided in polynomial time. G is 2 -colorable iff G is bipartite! Chandra & Manoj (UIUC) CS374 9 Fall 2015 9 / 57
Graph Coloring Observation: If G is colored with k colors then each color class (nodes of same color) form an independent set in G . Thus, G can be partitioned into k independent sets iff G is k -colorable. Graph 2 -Coloring can be decided in polynomial time. G is 2 -colorable iff G is bipartite! There is a linear time algorithm to check if G is bipartite using BFS Chandra & Manoj (UIUC) CS374 9 Fall 2015 9 / 57
Graph Coloring and Register Allocation Register Allocation Assign variables to (at most) k registers such that variables needed at the same time are not assigned to the same register Interference Graph Vertices are variables, and there is an edge between two vertices, if the two variables are “live” at the same time. Observations [Chaitin] Register allocation problem is equivalent to coloring the interference graph with k colors Moreover, 3-COLOR ≤ P k-Register Allocation , for any k ≥ 3 Chandra & Manoj (UIUC) CS374 10 Fall 2015 10 / 57
Class Room Scheduling Given n classes and their meeting times, are k rooms sufficient? Chandra & Manoj (UIUC) CS374 11 Fall 2015 11 / 57
Class Room Scheduling Given n classes and their meeting times, are k rooms sufficient? Reduce to Graph k -Coloring problem Create graph G a node v i for each class i an edge between v i and v j if classes i and j conflict Chandra & Manoj (UIUC) CS374 11 Fall 2015 11 / 57
Class Room Scheduling Given n classes and their meeting times, are k rooms sufficient? Reduce to Graph k -Coloring problem Create graph G a node v i for each class i an edge between v i and v j if classes i and j conflict Exercise: G is k -colorable iff k rooms are sufficient Chandra & Manoj (UIUC) CS374 11 Fall 2015 11 / 57
Frequency Assignments in Cellular Networks Cellular telephone systems that use Frequency Division Multiple Access (FDMA) (example: GSM in Europe and Asia and AT&T in USA) Breakup a frequency range [ a , b ] into disjoint bands of frequencies [ a 0 , b 0 ] , [ a 1 , b 1 ] , . . . , [ a k , b k ] Each cell phone tower (simplifying) gets one band Constraint: nearby towers cannot be assigned same band, otherwise signals will interference Chandra & Manoj (UIUC) CS374 12 Fall 2015 12 / 57
Frequency Assignments in Cellular Networks Cellular telephone systems that use Frequency Division Multiple Access (FDMA) (example: GSM in Europe and Asia and AT&T in USA) Breakup a frequency range [ a , b ] into disjoint bands of frequencies [ a 0 , b 0 ] , [ a 1 , b 1 ] , . . . , [ a k , b k ] Each cell phone tower (simplifying) gets one band Constraint: nearby towers cannot be assigned same band, otherwise signals will interference Problem: given k bands and some region with n towers, is there a way to assign the bands to avoid interference? Can reduce to k -coloring by creating intereference/conflict graph on towers. Chandra & Manoj (UIUC) CS374 12 Fall 2015 12 / 57
3 color this gadget. You are given three colors: red, green and blue. Can the following graph be three colored in a valid way (assuming that some of the nodes are already colored as indicated). (A) Yes. (B) No. Chandra & Manoj (UIUC) CS374 13 Fall 2015 13 / 57
3 color this gadget II You are given three colors: red, green and blue. Can the following graph be three colored in a valid way (assuming that some of the nodes are already colored as indicated). (A) Yes. (B) No. Chandra & Manoj (UIUC) CS374 14 Fall 2015 14 / 57
3-Coloring is NP-Complete 3-Coloring is in NP . Non-deterministically guess a 3-coloring for each node Check if for each edge ( u , v ) , the color of u is different from that of v . Hardness: We will show 3-SAT ≤ P 3-Coloring . Chandra & Manoj (UIUC) CS374 15 Fall 2015 15 / 57
Reduction Idea Start with 3SAT formula (i.e., 3 CNF formula) ϕ with n variables x 1 , . . . , x n and m clauses C 1 , . . . , C m . Create graph G ϕ such that G ϕ is 3-colorable iff ϕ is satisfiable need to establish truth assignment for x 1 , . . . , x n via colors for some nodes in G ϕ . Chandra & Manoj (UIUC) CS374 16 Fall 2015 16 / 57
Reduction Idea Start with 3SAT formula (i.e., 3 CNF formula) ϕ with n variables x 1 , . . . , x n and m clauses C 1 , . . . , C m . Create graph G ϕ such that G ϕ is 3-colorable iff ϕ is satisfiable need to establish truth assignment for x 1 , . . . , x n via colors for some nodes in G ϕ . create triangle with node True, False, Base Chandra & Manoj (UIUC) CS374 16 Fall 2015 16 / 57
Reduction Idea Start with 3SAT formula (i.e., 3 CNF formula) ϕ with n variables x 1 , . . . , x n and m clauses C 1 , . . . , C m . Create graph G ϕ such that G ϕ is 3-colorable iff ϕ is satisfiable need to establish truth assignment for x 1 , . . . , x n via colors for some nodes in G ϕ . create triangle with node True, False, Base for each variable x i two nodes v i and ¯ v i connected in a triangle with common Base Chandra & Manoj (UIUC) CS374 16 Fall 2015 16 / 57
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