Inputs. Outputs. Outputs. Inputs. Outputs. Inputs

Size: px
Start display at page:

Download "Inputs. Outputs. Outputs. Inputs. Outputs. Inputs"

Transcription

1 Permutation Admissibility in Shue-Exchange Networks with Arbitrary Number of Stages Nabanita Das Bhargab B. Bhattacharya Rekha Menon Indian Statistical Institute Calcutta, India Sergei L. Bezrukov Dept. of Math. & CS University of Paderborn 9 Paderborn Germany sb@uni-paderborn.de Abstract The set of input-output permutations that are routable through a multistage interconnection network without any conict (known as the admissible set), plays an important role in determining the capability of the network. Recent works on the permutation admissibity problem of shueexchange networks (SEN) of size N N, deal with (n + k) stages, where n = log N, and k denotes the number of extra stages. For k = or, O(Nn) algorithms exist to check if any permutation is admissible, but for k, a polynomial time solution is not yet known. The more general problem of nding the minimum number (m) of shueexchange stages required to realize an arbitrary permutation, m n?, is also an open problem. In this paper, we present an O(Nn) algorithm that checks whether a given permutation P is admissible in an m stage SEN, m n, and determines in O(Nnlogn) time the minimum number of stages m of shue-exchange, required to realize P. Thus, a single-stage shue-exchange network will be able to realize such a permutation with m passes, by recirculating all the paths m times through a single-stage, i.e., with minimum transmission delay, which, otherwise cannot be achieved with a xed-stage SEN. Furthermore, we present a necessary condition for permutation admissibility in an m stage SEN, where n < m n?. Introduction An n-stage multistage interconnection network (MIN) of size N N, where N = n, for n, is a minimal full-access unique-path structure, since it provides exactly one path from any source to any destination, e.g., omega, baseline, cube and reverse-baseline [-]. However, they are inherently blockinn nature, i.e., to connect more than one source-destination pairs simultaneously, a single link may be demanded by two or more paths, causing conicts. To overcome this problem, as well as to provide some fault-tolerance, k-extra-stage MIN's (i.e., with (n + k) stages), were proposed, which provide k paths between any inputoutput pair [-8]. An N N permutation from the set of N inputs (; ; :::; N? ) to the set of N outputs (; ; :::; N? ) is said to be admissible, if N conict-free paths (one for each input-output pair) can be set up simultaneously in the MIN. In [], it has been reported that a permutation is admissible in a k-extra-stage SEN if and only if the conict graph is k -colorable, and since the c-coloring (c > ) problem in graphs is NPcomplete, the complexity of determining permutation admissibility in a k-extra-stage MIN, for k, is not known. For k = or, O(Nn) algorithms were reported for checking permutation admissibility, but in general, the problem remains open [,]. In this paper, we address the following more general problem: given any N N permutation P, check whether P is admissible in an m stage SEN, for m n. Our proposed algorithm ascertains this in O(Nn) time, and also nds the minimum number of stages (m) of shue-exchange, for which P is admissible, in O(N nlogn) time. Our technique will be especially applicable to a network implemented with a single-stage shue-exchange, where permutations are realized by recirculation. In other words, if a permutation P is admissible in m stages, m n, recirculating the paths m times through a single-stage shue-exchange network, one can realize P, with minimum transmission delay. This is not possible otherwise, with a multistage shue-exchange network having a xed number of stages. We explore some new results on admissibility, for stages m, n < m n?. Since a (n? )-stage shue-exchange network is rearrangeable, one can realize any arbitrary permutation in (n? ) stages of shue-exchange []. We formulate a necessary condition that a permutation P must satisfy for being admissible on an m stage SEN, for n < m n?. This gives a lower bound on the number of recirculation stages of shue-exchange required to make P admissible. The paper is organized as follows. In Section, we analyze some properties of m-stage N N SEN, m n?, and characterize the set of admissible permutations for any m. In Section, we propose an algorithm to solve the permutation admissibility problem in an m-stage SEN, m n, and show how it can be applied to nd the lower bound of m required to make any arbitrary permutation admissible. Conclusions and further discussons appear in Section

2 . Input-Output Groups and Permutation Admissibility An N N multistage interconnection network, in general, consists of n stages, which is essentially a minimal structure that provides full-accessability with exactly one path for any input-output pair. Now, to provide some fault-tolerance, as well as to enhance the set of permutations admissible on the MIN, k-extra stages are added to it. Since, in a SEN, the connection patterns between adjacent stages are always the same, the sets of permutations admissible in an m-stage SEN, for m n? exhibit many elegant properties.. Motivating Examples Let us consider an (8 8) m-stage SEN, and dierent admissible permutations for various m, m. Example : The permutation P : SEN with m =. Fig. shows the paths for P on a single-stage SEN. It is to be noted that though P is admissible in a single-stage SEN, it is not admissible in SEN's with, or -stages. Figure : Paths for permutation P Figure : Paths for permutation P Remark The identity permutation is always admissible in an n-stage N N SEN. Example : The permutation P :, is admissible in a SEN with m =. Fig. shows the paths on a -stage SEN. Here stages are essential to make P admissible. Figure : Paths for permutation P Example : The permutation P : SEN with m =. Fig. shows the paths on a -stage SEN. Note that P is admissible neither in a single-stage SEN, nor in a -stage SEN. Example : The permutation P : SEN with m =. Fig. shows the paths on a -stage SEN. Note that P is the identity permutation, and minimum (= n) stages are necessary to make it admissible. Figure : Paths for permutation P Example : The permutation P : SEN with m =. Fig. shows the paths on a - stage SEN. Note that minimum stages are required to make P admissible. Therefore, it is clear from the above examples that

3 Figure : Paths for permutation P instead of using a xed-stage SEN, we can use a singlestage SEN, and recirculate the paths, for routing any arbitrary permutation P with minimum delay, provided m, the minimum number of stages of SEN, required to make P admissible, is known.. Group Structures Here, we will use the idea of group structures for analyzing the relations between input (output) groups and permutation admissibilty of a SEN. The concept of input (output) group structures for MIN's was introduced earlier in [9, ]. For completeness, we give a brief description of the input (output) group structures for SEN. In an m stage N N SEN, m n?, inputs (or outputs) are labeled as: ; ; :::; N? respectively, from top to bottom, and each is represented uniquely by an n bit binary string; the stages are labelled as: ; ; ::::; (m? ), from the input side towards the output side; the output links of each stage are labeled as: ; ; ::::; (N? ), from top to bottom. A SEN with N = 8 and m = is shown in Fig.. i.e., n?j < p, and r = or, for n < r n? j. Here gi (j; p) will be represented as ( j x n?j? :::x ), where j is a string of j 's, and (x n?j? :::x ) is the binary string representing p. Example : For a SEN an input group (; ) = ( ) = (; ; ; ) = (; ; ; ). Denition Similarly, for an N N SEN, an output group g o (j; p) denes a group of j outputs at level j, j n, given by x n? x n? :::x j j? j? :::, where (x n? :::x j ) is the binary representation of p i.e., n?j < p, and r = or, for < r j?, and will be represented by (x n? x n? :::x j j ). Example : For an SEN an output group g o (; ) = ( ) = (; ; ; ; = (; ; ; ). For an 88 SEN, the input and output group structures are shown in Fig.. a) b) (,,,,,,, ) (,) (,) (,,, ) (,,, ) (,) (,) (,) (,) (, ) (, ) (, ) (, ) (,,,,,,, ) Stage: Figure : A -stage 8 8 SEN with link labels Denition For an N N SEN, an input group (j; p) at level j, j n, denes a group of j inputs given by n? n? :::: n?j x n?j? x n?j? :::x x, where x n?j? ::::x x is the binary representation of p, (,) (,) (,,, ) (,,, ) (,) (,) (,) (,) (, ) (, ) (, ) (, ) Figure : (a) Input and (b) output groups of an 8 8 SEN Next we consider the permutation admissibility problem in an N N SEN, with m stages, for m n?. Denition For an N N SEN, with m stages, for m n?, given any N N permutation P, we construct an N (n+m) binary matrix M, where each

4 row x n? x n? :::x x :::: m represents one inputoutput path x! y; x n? x n? :::x x is the input x, and the bits :::: m, are determined by the output y, and the number of stages m; and a window W j ; j < m, is the set of n consecutive columns of M, x n?j? :::x x :::: j, and each row of W j is the link, the path follows at the output of stage j. The matrix M is dened as the path matrix of P, in an m-stage SEN. Fig. 8 shows the path matrix M for the permutation P, of Example, and the corresponding windows for a -stage 8 8 SEN. But this set is the output group g o (m; p), where p = (x n?m? :::x x ). Now it is evident that for any input in the group (m; p) = ( m x n?m? :::x x ), the reachable set will be the same group g o (m; p), for p < n?m : Hence the proof. Corollary In an m stage N N SEN, < m < n, an output y = y n? y n? :::y y is reachable from an input x = x n? x n? :::x x, if and only if y n?j = x n?m?j, for 8j; j n? m. Proof : Follows directly from Lemma. W W Denition In an m-stage N N SEN, < m n, if an output y is reachable from an input x, the path x! y is said to be a realizable path. M = x x x * = y * = y Figure 8: The path matrix for permutation P in a -stage 8 8 SEN Remark A permutation P is admissible in an m stage N N SEN, if and only if there exists a path matrix M, where all the rows are distinct in each window W j, j < m. We study the two cases separately: one for < m n and the other with n < m n?.. m-stage N N SEN, m n In this case, the network is not a full-access one, except when m = n. Starting from any input one can reach only a particular set of m ( N) outputs. However, given any input-output pair, if a path exists, it is always unique. Denition For an m-stage N N SEN, < m n, the set of outputs which can be reached from an input x is referred to as the reachable set of the input x. Lemma In an m-stage N N SEN, < m n, for any input x (m; p), the reachable set is the output group g o (m; p), where n?m < p. Proof : Let us consider an N N SEN with m stages, < m n. Now starting from any input, say x = x n? x n? :::x x, at each stage it may follow either a shue or a shue-exchange. Therefore, after the rst stage, x may reach any output represented by : (x n? :::x x ), where = x n? or x n?, i.e., = or. Now after m successive stages x may reach the set of outputs represented as (y = x n?m? :::x x m ). Remark In an m-stage N N SEN, m n, if an output y = y n? y n? :::y y is reachable from an input x = x n? x n? :::x x, in the path matrix M, the path x! y is represented by the string of (n+m) bits: x! y : x n? x n? :::x x y m? y m? :::y y, where the window (x n?j? x n?j? :::x x y m? y m? :::y m?j? ), is the binary representation of the link label, the path follows at any stage j, j < m. By Corollary, we can represent the same path as x! y : x n? x n? :::x n?m y n? :::y y. The above result conforms with similar results established in [,], for m = n only. Example 8 : In a -stage SEN, a path! is shown in Fig. 9a. The path is represented as ()! () :, the four bits from the left (right) represents the input, (output ), and the two overlap in the middle bit. The links followed by the path in stages ; ; are (), (), and () respectively, as given by the respective windows, are shown in Fig. 9b. Therefore, for an m-stage N N SEN, m n, given any permutation P, if all input-output paths are realizable, the set of N paths is represented by a N (n + m) path matrix M, where each row stands for one input-output path, as explained earlier. Now P will be admissible in the SEN, if and only if all the rows in every window W j, j < m, are distinct. Denition In an N N SEN, two inputs (outputs) x and x are said to be covered by an input (output) group (o) (j; p) if x ; x belong to the same input (output) group at level j, j n, but in dierent groups at level (j? ). Example 9 : For a SEN, two inputs 8() and () are covered by (; ), i.e., the group ( ). Remark In an N N SEN, two inputs (outputs) x and x covered by an input (output) group =o (j; p) must dier in bit x n?j (x j ).

5 a) conictinn stage (j? ), where they both need the same link (x n?j? ::x n?m? :::x x y m? ::y m?j ): They may also conict in a following stage (j + k? ), k < m? j, if ym?j?r = y m?j?r; 8r; r k: Only if: Let y and y belong to two dierent output groups at level (m? j), say g o (m? j; p), and g o (m? j; p ); p = p : Let p = (y n? :::y m?j ), and p = (y n? :::y m?j ); they will dier at least in one bit position. The two paths will never conict at any stage-k, for k < m. Hence the proof. Theorem In an m-stage N N SEN ( m n), a permutation P is admissible if and only if i) each input is mapped to a reachable output, and ii) the j inputs of an input group at level j, j m are mapped to outputs such that exactly one of them belongs to a unique output group at level (m? j). Proof: Follows directly from Lemma. b) W W W Figure 9: (a) The path! in a -stage SEN, and (b) the windows in each stage Lemma In an m-stage N N SEN, ( m n), two realizable paths x! y and x! y will be conictinf and only if for x; x covered by an input group at level j; j m, y; y belong to the same group at level (m? j): Proof : Let x = x n? x n? :::x x. Then by Remark, x = x n? ::x x n?j+ n?jx n?j? :::x x, since they are covered by an input group at level j; j < m. Now since y is reachable for x, by Corollary, y = x n?m? x n?m? :::x x y m? y m? :::y y. Similarly, y = x n?m? x n?m? :::x x y m? y m? :::y y : Now the two paths can be represented as: x! y : x n? ::x n?m? :::x x y m? y m? :::y y, and x! y :x n? ::x x n?j+ n?jx n?j? ::x n?m? ::x y m? ::y : It is evident that these two paths will never conict at any stage k, for k j?, since x n?j = x n?j. If part: If the corresponding outputs y and y are in the same output group at level (m? j), y = x n?m? x n?m? :::x x y m? ::y m?j y m?j? :::y y. The two paths under consideration become: x! y : x n? ::x n?m? :::x x y m? ::y m?j :::y y, and x! y : x n?::x x n?j+ n?jx n?j? ::x n?m? :::x y m? ::y m?j y m?j? :::y. Now it is obvious that these two paths will be always Denition For an N N SEN, the i-admissible set of permutations i is dened as the set of all permutations admissible in i stages, where, i n. We use a notation to represent input-output mapping rules as follows: The mapping f (j; p )j (j; p )j:::j (j; p r )g! fg o (m? j; q ); g o (m? j; q ); :::; g o (m? j; q j )g, implies that each element of any input group (j; p u ); u r, is mapped to an output of a unique group g o (m? j; q v ); v j. Example : In an 8 8 SEN, where n =, let us compute the i-admissible sets of permutations i, for i. From Theorem : For any permutation P : for (; p): f(; )g! f(); ()g, f(; )g! f(); ()g, f(; )g! f(); ()g, and f(; )g! f(); ()g, Hence, the permutation P :. For any permutation P : for (; p): f(; )j(; )g! f(; ); (; )g, f(; )j(; )g! f(; ); (; )g, for (; p):f(; ; ; )g! f(); (); (); ()g, f(; ; ; )g! f(); (); (); ()g e.g., the permutation P :. Note that P = : For any permutation P : for (; p): f(; )j(; )j(; )j(; )g! f(; ; ; ); (; ; ; )g for (; p): f(; ; ; )j(; ; ; )g!

6 f(; ); (; ); (; ); (:)g, for (; p): f(; ; ; ; ; ; ; )g! f(); (); (); (); (); (); (); ()g e.g., the permutation P :. Note that P ; P = : The path matrix for P, in a -stage SEN is shown in Fig. 8. Note that in each case, all the rows in every possible window are distinct, proving that all the paths are conict-free, i.e., the permutations are admissible. Corollary In an m-stage N N SEN, all the i- admissible sets of permutations are disjoint. Proof : Follows directly from Theorem. In the next section, an O(Nn) algorithm has been proposed to determine whether or not an arbitrary N N permutation P is admissible in an m-stage N N SEN ( m n). Formerly, an algorithm with the same complexity was reported only for an n-stage SEN [].. m-stage N N SEN, n m n? In this case, the network is full-access, i.e., each input can reach any output, but instead of a uniquepath there exist m?n paths between any pair of input-output. Now we may represent an inputoutput path x! y, as a sequence of (n + m) bits, (x n? x n? :::x x ::: n?m y n? ::y y ), where (x n? x n? :::x x ) is the binary representation of the input x, and (y n? ::y y ) represents the output y; the (m? n) bits between the two, represented as ( ::: m?n ) are arbitrary. In fact, each possible combination of these bits, represents a path from x to y. Therefore, a given permutation P, is admissible in an m stage N N SEN, n m n?, if and only if there exists an assignment for all the bits ( ::: m?n ), such that all rows in each window W j, j < m, of the path matrix M are distinct. Example : Fig. shows a possible path matrix for the permutation P :, on a -stage 8 8 SEN. Note that all the rows in each window W j, j, are distinct. Theorem If an N N permutation P is admissible in an m-stage N N SEN, n m n?, then in P, the j inputs of each input group at level j, m?n < j n are mapped to outputs such that exactly m?n of them belong to the same output group at level (m? j). Proof : Let us consider a permutation P, such that there is at least one input group at level j, m? n < j n, of which more than m?n inputs are mapped to outputs belonging to the same output M = W W W W x x x * * y y y Figure : Path matrix for permutation P group at level (m? j). Now let us consider the window W j?, which consists of the bit string x n?j? :::x :: m?n y n? :::y m?j for each path of P. For any input group at level j, all the inputs consists of an identical bit string x n?j? :::x. Now if more than m?n inputs of the group are mapped to the outputs in the same output group at level (m? j), they will have identical bit string y n? :::y m?j. This will result more than m?n rows of W j? with identical bit strings for the part x n?j? ::x, as well as for y n? ::y m?j. Now, by using the bits ; :::; m?n, we can make at most m?n rows dierent. Hence for P, in W j?, there will be more than one identical rows for any possible assignments of ::: m?n. Hence the proof. Algorithms First, we present an algorithm that will decide if a given permutation P is admissible in an m-stage N N SEN, m n. The permutation is given as an array out of length N, such that out(i) stores the output corresponding to the input i, i N?. Algorithm : Admissibility Check Input: n, m, out(n) Output: success Step : success := Step : for x = : : : N?, if xmod( n?m ) = out(x)div m then terminate (* to check reachability *); Step : for i = : : : m for p = : : : ( i?? ) for x = p: n?i+ : : : (p: n?i+ + n?i? ) if out(x) and out(x + n?i ) rst dier in bit x m?i, when compared from MSB, then if out(x) > out(x + n?i ), exchange them in array out;

7 Step : next x else terminate; next p next i success:=, terminate; The above algorithm is of time complexity O(N n). Now given any permutation P, admissible on an i- stage SEN, i n, to nd the minimum number of stages m necessary to make P admissible, we can perform a binary search over the interval to i by invoking the above algorithm at most logn times. Therefore, m can be determined in O(N nlogn) time. Conclusion We have shown that the permutation admissibility problem for an m-stage shue-exchange network can be solved for m n, in O(Nn) time, which was formerly solved only for m = n and (n + ) [,]. This algorithm also helps us to nd the minimum number of stages m; m n of a SEN, necessary to make such a permutation admissible, with a complexity O(N nlogn). Therefore, by using a single-stage SEN, we can recirculate the paths m times through the network, to realize such a permutation P. This technique enables us to route the permutation through the network with minimum transmission delay. For n < m n?, we establish a necessary condition that a permutation P must satisfy for being admissible in an m stage SEN. It gives a lower bound on the number of stages required for making P admissible. References [] X. Shen, M. Xu, and X. Wang, \An optimal algorithm for permutation admissibility to multistage interconnection networks," IEEE Trans. Computers, vol., no., pp. -8, Apr. 99. [] X. Shen, \An optimal O(NlgN) algorithm for permutation admissibility to extra-stage cube-type networks," IEEE Trans. Computers, vol., no. 9, pp. -9, Sep. 99. [] A. Abdendher and T. Feng, \On rearrangeability of Omega-Omega networks," Proc. 99 Int'l Conf. Parallel Processing, pp. I-9-, 99. [] C. L. Wu and T. Feng, \On a class of multistage interconnection networks," IEEE Trans. Computers, vol. C-9, no. 8, pp. 9-, Aug. 98. [] H. S. Stone, \ Parallel processing with the perfect shuf- e," IEEE Trans. Computers, vol. C-, no., pp.-, Feb. 9. [] C. L. Wu and T. Feng, \The universality of the shueexchange network,"ieee Trans. Computers, vol., no. 8, pp. -, May 98. [] C. S. Raghavendra and A. Varma, \Fault-tolerant multiprocessors with redundant path networks," IEEE Trans. Computers, vol. C-, no., pp. -, April 98. [8] N. Das, B. B. Bhattacharya and J. Dattagupta, \Isomorphism of conict graphs in multistage interconnection networks and its application to optimal routing," IEEE Trans. Computers, vol., no., pp. -, June 99. [9] N. Das, B. B. Bhattacharya and J. Dattagupta, \Hierarchical classication of permutation classes in multistage interconnection networks," IEEE Trans. Computers, vol., no., pp. 9-, Dec. 99.

Lossy Compression of Permutations

Lossy Compression of Permutations 204 IEEE International Symposium on Information Theory Lossy Compression of Permutations Da Wang EECS Dept., MIT Cambridge, MA, USA Email: dawang@mit.edu Arya Mazumdar ECE Dept., Univ. of Minnesota Twin

More information

O(n) routing in rearrangeable networks

O(n) routing in rearrangeable networks Journal of Systems Architecture 46 (2000) 529±542 www.elsevier.com/locate/sysarc O(n) routing in rearrangeable networks Nabanita Das, Krishnendu Mukhopadhyaya, Jayasree Dattagupta * HACM Unit, Indian Statistical

More information

CENTRALIZED BUFFERING AND LOOKAHEAD WAVELENGTH CONVERSION IN MULTISTAGE INTERCONNECTION NETWORKS

CENTRALIZED BUFFERING AND LOOKAHEAD WAVELENGTH CONVERSION IN MULTISTAGE INTERCONNECTION NETWORKS CENTRALIZED BUFFERING AND LOOKAHEAD WAVELENGTH CONVERSION IN MULTISTAGE INTERCONNECTION NETWORKS Mohammed Amer Arafah, Nasir Hussain, Victor O. K. Li, Department of Computer Engineering, College of Computer

More information

Math236 Discrete Maths with Applications

Math236 Discrete Maths with Applications Math236 Discrete Maths with Applications P. Ittmann UKZN, Pietermaritzburg Semester 1, 2012 Ittmann (UKZN PMB) Math236 2012 1 / 43 The Multiplication Principle Theorem Let S be a set of k-tuples (s 1,

More information

Non-overlapping permutation patterns

Non-overlapping permutation patterns PU. M. A. Vol. 22 (2011), No.2, pp. 99 105 Non-overlapping permutation patterns Miklós Bóna Department of Mathematics University of Florida 358 Little Hall, PO Box 118105 Gainesville, FL 326118105 (USA)

More information

PARTITIONING PERMUTATION NETWORKS: THE UNDERLYING THEORY

PARTITIONING PERMUTATION NETWORKS: THE UNDERLYING THEORY PARTITIONING PERMUTATION NETWORKS: THE UNDERLYING THEORY Howard Jay Siegel Purdue University School of Electrical Engineering West Lafayette, IN 47907 Abstract The age of the microcomputer has made feasible

More information

arxiv: v1 [cs.cc] 21 Jun 2017

arxiv: v1 [cs.cc] 21 Jun 2017 Solving the Rubik s Cube Optimally is NP-complete Erik D. Demaine Sarah Eisenstat Mikhail Rudoy arxiv:1706.06708v1 [cs.cc] 21 Jun 2017 Abstract In this paper, we prove that optimally solving an n n n Rubik

More information

Greedy Flipping of Pancakes and Burnt Pancakes

Greedy Flipping of Pancakes and Burnt Pancakes Greedy Flipping of Pancakes and Burnt Pancakes Joe Sawada a, Aaron Williams b a School of Computer Science, University of Guelph, Canada. Research supported by NSERC. b Department of Mathematics and Statistics,

More information

Pattern Avoidance in Unimodal and V-unimodal Permutations

Pattern Avoidance in Unimodal and V-unimodal Permutations Pattern Avoidance in Unimodal and V-unimodal Permutations Dido Salazar-Torres May 16, 2009 Abstract A characterization of unimodal, [321]-avoiding permutations and an enumeration shall be given.there is

More information

each pair of constellation points. The binary symbol error that corresponds to an edge is its edge label. For a constellation with 2 n points, each bi

each pair of constellation points. The binary symbol error that corresponds to an edge is its edge label. For a constellation with 2 n points, each bi 36th Annual Allerton Conference on Communication, Control, and Computing, September 23-2, 1998 Prole Optimal 8-QAM and 32-QAM Constellations Xueting Liu and Richard D. Wesel Electrical Engineering Department

More information

Ecient Routing in Optical Networks. Alok Aggarwal Amotz Bar-Noy Don Coppersmith. Rajiv Ramaswami Baruch Schieber Madhu Sudan. IBM { Research Division

Ecient Routing in Optical Networks. Alok Aggarwal Amotz Bar-Noy Don Coppersmith. Rajiv Ramaswami Baruch Schieber Madhu Sudan. IBM { Research Division Ecient Routing in Optical Networks Alok Aggarwal Amotz Bar-Noy Don Coppersmith Rajiv Ramaswami Baruch Schieber Madhu Sudan IBM { Research Division T. J. Watson Research Center Yorktown Heights, NY 10598

More information

Bounding the Size of k-tuple Covers

Bounding the Size of k-tuple Covers Bounding the Size of k-tuple Covers Wolfgang Bein School of Computer Science Center for the Advanced Study of Algorithms University of Nevada, Las Vegas bein@egr.unlv.edu Linda Morales Department of Computer

More information

Binary Continued! November 27, 2013

Binary Continued! November 27, 2013 Binary Tree: 1 Binary Continued! November 27, 2013 1. Label the vertices of the bottom row of your Binary Tree with the numbers 0 through 7 (going from left to right). (You may put numbers inside of the

More information

Fast Sorting and Pattern-Avoiding Permutations

Fast Sorting and Pattern-Avoiding Permutations Fast Sorting and Pattern-Avoiding Permutations David Arthur Stanford University darthur@cs.stanford.edu Abstract We say a permutation π avoids a pattern σ if no length σ subsequence of π is ordered in

More information

A FAMILY OF t-regular SELF-COMPLEMENTARY k-hypergraphs. Communicated by Behruz Tayfeh Rezaie. 1. Introduction

A FAMILY OF t-regular SELF-COMPLEMENTARY k-hypergraphs. Communicated by Behruz Tayfeh Rezaie. 1. Introduction Transactions on Combinatorics ISSN (print): 2251-8657, ISSN (on-line): 2251-8665 Vol. 6 No. 1 (2017), pp. 39-46. c 2017 University of Isfahan www.combinatorics.ir www.ui.ac.ir A FAMILY OF t-regular SELF-COMPLEMENTARY

More information

An Optimal (d 1)-Fault-Tolerant All-to-All Broadcasting Scheme for d-dimensional Hypercubes

An Optimal (d 1)-Fault-Tolerant All-to-All Broadcasting Scheme for d-dimensional Hypercubes An Optimal (d 1)-Fault-Tolerant All-to-All Broadcasting Scheme for d-dimensional Hypercubes Siu-Cheung Chau Dept. of Physics and Computing, Wilfrid Laurier University, Waterloo, Ontario, Canada, N2L 3C5

More information

Stanford University CS261: Optimization Handout 9 Luca Trevisan February 1, 2011

Stanford University CS261: Optimization Handout 9 Luca Trevisan February 1, 2011 Stanford University CS261: Optimization Handout 9 Luca Trevisan February 1, 2011 Lecture 9 In which we introduce the maximum flow problem. 1 Flows in Networks Today we start talking about the Maximum Flow

More information

Zhan Chen and Israel Koren. University of Massachusetts, Amherst, MA 01003, USA. Abstract

Zhan Chen and Israel Koren. University of Massachusetts, Amherst, MA 01003, USA. Abstract Layer Assignment for Yield Enhancement Zhan Chen and Israel Koren Department of Electrical and Computer Engineering University of Massachusetts, Amherst, MA 0003, USA Abstract In this paper, two algorithms

More information

Determinants, Part 1

Determinants, Part 1 Determinants, Part We shall start with some redundant definitions. Definition. Given a matrix A [ a] we say that determinant of A is det A a. Definition 2. Given a matrix a a a 2 A we say that determinant

More information

How (Information Theoretically) Optimal Are Distributed Decisions?

How (Information Theoretically) Optimal Are Distributed Decisions? How (Information Theoretically) Optimal Are Distributed Decisions? Vaneet Aggarwal Department of Electrical Engineering, Princeton University, Princeton, NJ 08544. vaggarwa@princeton.edu Salman Avestimehr

More information

Tiling Problems. This document supersedes the earlier notes posted about the tiling problem. 1 An Undecidable Problem about Tilings of the Plane

Tiling Problems. This document supersedes the earlier notes posted about the tiling problem. 1 An Undecidable Problem about Tilings of the Plane Tiling Problems This document supersedes the earlier notes posted about the tiling problem. 1 An Undecidable Problem about Tilings of the Plane The undecidable problems we saw at the start of our unit

More information

Ecient Routing and Scheduling Algorithms. for Optical Networks. Alok Aggarwal Amotz Bar-Noy Don Coppersmith

Ecient Routing and Scheduling Algorithms. for Optical Networks. Alok Aggarwal Amotz Bar-Noy Don Coppersmith Ecient Routing and Scheduling Algorithms for Optical Networks Alok Aggarwal Amotz Bar-Noy Don Coppersmith Rajiv Ramaswami Baruch Schieber Madhu Sudan IBM { Research Division T. J. Watson Research Center

More information

An improvement to the Gilbert-Varshamov bound for permutation codes

An improvement to the Gilbert-Varshamov bound for permutation codes An improvement to the Gilbert-Varshamov bound for permutation codes Yiting Yang Department of Mathematics Tongji University Joint work with Fei Gao and Gennian Ge May 11, 2013 Outline Outline 1 Introduction

More information

On Drawn K-In-A-Row Games

On Drawn K-In-A-Row Games On Drawn K-In-A-Row Games Sheng-Hao Chiang, I-Chen Wu 2 and Ping-Hung Lin 2 National Experimental High School at Hsinchu Science Park, Hsinchu, Taiwan jiang555@ms37.hinet.net 2 Department of Computer Science,

More information

1. Introduction: Multi-stage interconnection networks

1. Introduction: Multi-stage interconnection networks Manipulating Multistage Interconnection Networks Using Fundamental Arrangements E Gur and Z Zalevsky Faculty of Engineering, Shenkar College of Eng & Design, Ramat Gan,, Israel gureran@gmailcom School

More information

Compound Probability. Set Theory. Basic Definitions

Compound Probability. Set Theory. Basic Definitions Compound Probability Set Theory A probability measure P is a function that maps subsets of the state space Ω to numbers in the interval [0, 1]. In order to study these functions, we need to know some basic

More information

Decoding Distance-preserving Permutation Codes for Power-line Communications

Decoding Distance-preserving Permutation Codes for Power-line Communications Decoding Distance-preserving Permutation Codes for Power-line Communications Theo G. Swart and Hendrik C. Ferreira Department of Electrical and Electronic Engineering Science, University of Johannesburg,

More information

Lower Bounds for the Number of Bends in Three-Dimensional Orthogonal Graph Drawings

Lower Bounds for the Number of Bends in Three-Dimensional Orthogonal Graph Drawings ÂÓÙÖÒÐ Ó ÖÔ ÐÓÖØÑ Ò ÔÔÐØÓÒ ØØÔ»»ÛÛÛº ºÖÓÛÒºÙ»ÔÙÐØÓÒ»» vol.?, no.?, pp. 1 44 (????) Lower Bounds for the Number of Bends in Three-Dimensional Orthogonal Graph Drawings David R. Wood School of Computer Science

More information

Lectures: Feb 27 + Mar 1 + Mar 3, 2017

Lectures: Feb 27 + Mar 1 + Mar 3, 2017 CS420+500: Advanced Algorithm Design and Analysis Lectures: Feb 27 + Mar 1 + Mar 3, 2017 Prof. Will Evans Scribe: Adrian She In this lecture we: Summarized how linear programs can be used to model zero-sum

More information

Lecture 2. 1 Nondeterministic Communication Complexity

Lecture 2. 1 Nondeterministic Communication Complexity Communication Complexity 16:198:671 1/26/10 Lecture 2 Lecturer: Troy Lee Scribe: Luke Friedman 1 Nondeterministic Communication Complexity 1.1 Review D(f): The minimum over all deterministic protocols

More information

On uniquely k-determined permutations

On uniquely k-determined permutations On uniquely k-determined permutations Sergey Avgustinovich and Sergey Kitaev 16th March 2007 Abstract Motivated by a new point of view to study occurrences of consecutive patterns in permutations, we introduce

More information

The number of mates of latin squares of sizes 7 and 8

The number of mates of latin squares of sizes 7 and 8 The number of mates of latin squares of sizes 7 and 8 Megan Bryant James Figler Roger Garcia Carl Mummert Yudishthisir Singh Working draft not for distribution December 17, 2012 Abstract We study the number

More information

Juggling Networks. Nicholas Pippenger* The University of British Columbia. Vancouver, British Columbia V6T 1Z4 CANADA

Juggling Networks. Nicholas Pippenger* The University of British Columbia. Vancouver, British Columbia V6T 1Z4 CANADA Juggling Networks Nicholas Pippenger* e-mail: nicholas@cs.ubc.ca Department of Computer Science The University of British Columbia Vancouver, British Columbia V6T 1Z4 CANADA Abstract: Switching networks

More information

A NEW COMPUTATION OF THE CODIMENSION SEQUENCE OF THE GRASSMANN ALGEBRA

A NEW COMPUTATION OF THE CODIMENSION SEQUENCE OF THE GRASSMANN ALGEBRA A NEW COMPUTATION OF THE CODIMENSION SEQUENCE OF THE GRASSMANN ALGEBRA JOEL LOUWSMA, ADILSON EDUARDO PRESOTO, AND ALAN TARR Abstract. Krakowski and Regev found a basis of polynomial identities satisfied

More information

Integrated Strategy for Generating Permutation

Integrated Strategy for Generating Permutation Int J Contemp Math Sciences, Vol 6, 011, no 4, 1167-1174 Integrated Strategy for Generating Permutation Sharmila Karim 1, Zurni Omar and Haslinda Ibrahim Quantitative Sciences Building College of Arts

More information

THE use of balanced codes is crucial for some information

THE use of balanced codes is crucial for some information A Construction for Balancing Non-Binary Sequences Based on Gray Code Prefixes Elie N. Mambou and Theo G. Swart, Senior Member, IEEE arxiv:70.008v [cs.it] Jun 07 Abstract We introduce a new construction

More information

A Message Scheduling Scheme for All-to-all Personalized Communication on Ethernet Switched Clusters

A Message Scheduling Scheme for All-to-all Personalized Communication on Ethernet Switched Clusters A Message Scheduling Scheme for All-to-all Personalized Communication on Ethernet Switched Clusters Ahmad Faraj Xin Yuan Pitch Patarasuk Department of Computer Science, Florida State University Tallahassee,

More information

Noisy Index Coding with Quadrature Amplitude Modulation (QAM)

Noisy Index Coding with Quadrature Amplitude Modulation (QAM) Noisy Index Coding with Quadrature Amplitude Modulation (QAM) Anjana A. Mahesh and B Sundar Rajan, arxiv:1510.08803v1 [cs.it] 29 Oct 2015 Abstract This paper discusses noisy index coding problem over Gaussian

More information

Hamming Codes as Error-Reducing Codes

Hamming Codes as Error-Reducing Codes Hamming Codes as Error-Reducing Codes William Rurik Arya Mazumdar Abstract Hamming codes are the first nontrivial family of error-correcting codes that can correct one error in a block of binary symbols.

More information

Constructions of Coverings of the Integers: Exploring an Erdős Problem

Constructions of Coverings of the Integers: Exploring an Erdős Problem Constructions of Coverings of the Integers: Exploring an Erdős Problem Kelly Bickel, Michael Firrisa, Juan Ortiz, and Kristen Pueschel August 20, 2008 Abstract In this paper, we study necessary conditions

More information

Introduction. and Z r1 Z rn. This lecture aims to provide techniques. CRT during the decription process in RSA is explained.

Introduction. and Z r1 Z rn. This lecture aims to provide techniques. CRT during the decription process in RSA is explained. THE CHINESE REMAINDER THEOREM INTRODUCED IN A GENERAL KONTEXT Introduction The rst Chinese problem in indeterminate analysis is encountered in a book written by the Chinese mathematician Sun Tzi. The problem

More information

Game Theory and Algorithms Lecture 19: Nim & Impartial Combinatorial Games

Game Theory and Algorithms Lecture 19: Nim & Impartial Combinatorial Games Game Theory and Algorithms Lecture 19: Nim & Impartial Combinatorial Games May 17, 2011 Summary: We give a winning strategy for the counter-taking game called Nim; surprisingly, it involves computations

More information

X = {1, 2,...,n} n 1f 2f 3f... nf

X = {1, 2,...,n} n 1f 2f 3f... nf Section 11 Permutations Definition 11.1 Let X be a non-empty set. A bijective function f : X X will be called a permutation of X. Consider the case when X is the finite set with n elements: X {1, 2,...,n}.

More information

Graphs of Tilings. Patrick Callahan, University of California Office of the President, Oakland, CA

Graphs of Tilings. Patrick Callahan, University of California Office of the President, Oakland, CA Graphs of Tilings Patrick Callahan, University of California Office of the President, Oakland, CA Phyllis Chinn, Department of Mathematics Humboldt State University, Arcata, CA Silvia Heubach, Department

More information

CS256 Applied Theory of Computation

CS256 Applied Theory of Computation CS256 Applied Theory of Computation Parallel Computation III John E Savage Overview Mapping normal algorithms to meshes Shuffle operations on linear arrays Shuffle operations on two-dimensional arrays

More information

Scheduling Transmissions in WDM Optical Networks. throughputs in the gigabits-per-second range. That is, transmitters transmit data in xedlength

Scheduling Transmissions in WDM Optical Networks. throughputs in the gigabits-per-second range. That is, transmitters transmit data in xedlength Scheduling Transmissions in WDM Optical Networks Bhaskar DasGupta Department of Computer Science Rutgers University Camden, NJ 080, USA Michael A. Palis Department of Computer Science Rutgers University

More information

1.6 Congruence Modulo m

1.6 Congruence Modulo m 1.6 Congruence Modulo m 47 5. Let a, b 2 N and p be a prime. Prove for all natural numbers n 1, if p n (ab) and p - a, then p n b. 6. In the proof of Theorem 1.5.6 it was stated that if n is a prime number

More information

Recovery and Characterization of Non-Planar Resistor Networks

Recovery and Characterization of Non-Planar Resistor Networks Recovery and Characterization of Non-Planar Resistor Networks Julie Rowlett August 14, 1998 1 Introduction In this paper we consider non-planar conductor networks. A conductor is a two-sided object which

More information

NON-OVERLAPPING PERMUTATION PATTERNS. To Doron Zeilberger, for his Sixtieth Birthday

NON-OVERLAPPING PERMUTATION PATTERNS. To Doron Zeilberger, for his Sixtieth Birthday NON-OVERLAPPING PERMUTATION PATTERNS MIKLÓS BÓNA Abstract. We show a way to compute, to a high level of precision, the probability that a randomly selected permutation of length n is nonoverlapping. As

More information

1111: Linear Algebra I

1111: Linear Algebra I 1111: Linear Algebra I Dr. Vladimir Dotsenko (Vlad) Lecture 7 Dr. Vladimir Dotsenko (Vlad) 1111: Linear Algebra I Lecture 7 1 / 8 Invertible matrices Theorem. 1. An elementary matrix is invertible. 2.

More information

STRATEGY AND COMPLEXITY OF THE GAME OF SQUARES

STRATEGY AND COMPLEXITY OF THE GAME OF SQUARES STRATEGY AND COMPLEXITY OF THE GAME OF SQUARES FLORIAN BREUER and JOHN MICHAEL ROBSON Abstract We introduce a game called Squares where the single player is presented with a pattern of black and white

More information

How Many Mates Can a Latin Square Have?

How Many Mates Can a Latin Square Have? How Many Mates Can a Latin Square Have? Megan Bryant mrlebla@g.clemson.edu Roger Garcia garcroge@kean.edu James Figler figler@live.marshall.edu Yudhishthir Singh ysingh@crimson.ua.edu Marshall University

More information

Permutation Tableaux and the Dashed Permutation Pattern 32 1

Permutation Tableaux and the Dashed Permutation Pattern 32 1 Permutation Tableaux and the Dashed Permutation Pattern William Y.C. Chen, Lewis H. Liu, Center for Combinatorics, LPMC-TJKLC Nankai University, Tianjin 7, P.R. China chen@nankai.edu.cn, lewis@cfc.nankai.edu.cn

More information

A virtually nonblocking self-routing permutation network which routes packets in O(log 2 N) time

A virtually nonblocking self-routing permutation network which routes packets in O(log 2 N) time Telecommunication Systems 10 (1998) 135 147 135 A virtually nonblocking self-routing permutation network which routes packets in O(log 2 N) time G.A. De Biase and A. Massini Dipartimento di Scienze dell

More information

17. Symmetries. Thus, the example above corresponds to the matrix: We shall now look at how permutations relate to trees.

17. Symmetries. Thus, the example above corresponds to the matrix: We shall now look at how permutations relate to trees. 7 Symmetries 7 Permutations A permutation of a set is a reordering of its elements Another way to look at it is as a function Φ that takes as its argument a set of natural numbers of the form {, 2,, n}

More information

Bounds for Cut-and-Paste Sorting of Permutations

Bounds for Cut-and-Paste Sorting of Permutations Bounds for Cut-and-Paste Sorting of Permutations Daniel Cranston Hal Sudborough Douglas B. West March 3, 2005 Abstract We consider the problem of determining the maximum number of moves required to sort

More information

Chapter 3 PRINCIPLE OF INCLUSION AND EXCLUSION

Chapter 3 PRINCIPLE OF INCLUSION AND EXCLUSION Chapter 3 PRINCIPLE OF INCLUSION AND EXCLUSION 3.1 The basics Consider a set of N obects and r properties that each obect may or may not have each one of them. Let the properties be a 1,a,..., a r. Let

More information

Pattern Avoidance in Poset Permutations

Pattern Avoidance in Poset Permutations Pattern Avoidance in Poset Permutations Sam Hopkins and Morgan Weiler Massachusetts Institute of Technology and University of California, Berkeley Permutation Patterns, Paris; July 5th, 2013 1 Definitions

More information

Ecient Multichip Partial Concentrator Switches. Thomas H. Cormen. Laboratory for Computer Science. Massachusetts Institute of Technology

Ecient Multichip Partial Concentrator Switches. Thomas H. Cormen. Laboratory for Computer Science. Massachusetts Institute of Technology Ecient Multichip Partial Concentrator Switches Thomas H. Cormen Laboratory for Computer Science Massachusetts Institute of Technology Cambridge, Massachusetts 02139 Abstract Due to chip area and pin count

More information

Hypercube Networks-III

Hypercube Networks-III 6.895 Theory of Parallel Systems Lecture 18 ypercube Networks-III Lecturer: harles Leiserson Scribe: Sriram Saroop and Wang Junqing Lecture Summary 1. Review of the previous lecture This section highlights

More information

THE SIGN OF A PERMUTATION

THE SIGN OF A PERMUTATION THE SIGN OF A PERMUTATION KEITH CONRAD 1. Introduction Throughout this discussion, n 2. Any cycle in S n is a product of transpositions: the identity (1) is (12)(12), and a k-cycle with k 2 can be written

More information

Edge-disjoint tree representation of three tree degree sequences

Edge-disjoint tree representation of three tree degree sequences Edge-disjoint tree representation of three tree degree sequences Ian Min Gyu Seong Carleton College seongi@carleton.edu October 2, 208 Ian Min Gyu Seong (Carleton College) Trees October 2, 208 / 65 Trees

More information

An Enhanced Fast Multi-Radio Rendezvous Algorithm in Heterogeneous Cognitive Radio Networks

An Enhanced Fast Multi-Radio Rendezvous Algorithm in Heterogeneous Cognitive Radio Networks 1 An Enhanced Fast Multi-Radio Rendezvous Algorithm in Heterogeneous Cognitive Radio Networks Yeh-Cheng Chang, Cheng-Shang Chang and Jang-Ping Sheu Department of Computer Science and Institute of Communications

More information

Solutions to Exercises Chapter 6: Latin squares and SDRs

Solutions to Exercises Chapter 6: Latin squares and SDRs Solutions to Exercises Chapter 6: Latin squares and SDRs 1 Show that the number of n n Latin squares is 1, 2, 12, 576 for n = 1, 2, 3, 4 respectively. (b) Prove that, up to permutations of the rows, columns,

More information

Harmonic numbers, Catalan s triangle and mesh patterns

Harmonic numbers, Catalan s triangle and mesh patterns Harmonic numbers, Catalan s triangle and mesh patterns arxiv:1209.6423v1 [math.co] 28 Sep 2012 Sergey Kitaev Department of Computer and Information Sciences University of Strathclyde Glasgow G1 1XH, United

More information

Permutation group and determinants. (Dated: September 19, 2018)

Permutation group and determinants. (Dated: September 19, 2018) Permutation group and determinants (Dated: September 19, 2018) 1 I. SYMMETRIES OF MANY-PARTICLE FUNCTIONS Since electrons are fermions, the electronic wave functions have to be antisymmetric. This chapter

More information

RESTRICTED PERMUTATIONS AND POLYGONS. Ghassan Firro and Toufik Mansour Department of Mathematics, University of Haifa, Haifa, Israel

RESTRICTED PERMUTATIONS AND POLYGONS. Ghassan Firro and Toufik Mansour Department of Mathematics, University of Haifa, Haifa, Israel RESTRICTED PERMUTATIONS AND POLYGONS Ghassan Firro and Toufik Mansour Department of Mathematics, University of Haifa, 905 Haifa, Israel {gferro,toufik}@mathhaifaacil abstract Several authors have examined

More information

A combinatorial proof for the enumeration of alternating permutations with given peak set

A combinatorial proof for the enumeration of alternating permutations with given peak set AUSTRALASIAN JOURNAL OF COMBINATORICS Volume 57 (2013), Pages 293 300 A combinatorial proof for the enumeration of alternating permutations with given peak set Alina F.Y. Zhao School of Mathematical Sciences

More information

Two Models for Noisy Feedback in MIMO Channels

Two Models for Noisy Feedback in MIMO Channels Two Models for Noisy Feedback in MIMO Channels Vaneet Aggarwal Princeton University Princeton, NJ 08544 vaggarwa@princeton.edu Gajanana Krishna Stanford University Stanford, CA 94305 gkrishna@stanford.edu

More information

A tournament problem

A tournament problem Discrete Mathematics 263 (2003) 281 288 www.elsevier.com/locate/disc Note A tournament problem M.H. Eggar Department of Mathematics and Statistics, University of Edinburgh, JCMB, KB, Mayeld Road, Edinburgh

More information

Good Synchronization Sequences for Permutation Codes

Good Synchronization Sequences for Permutation Codes 1 Good Synchronization Sequences for Permutation Codes Thokozani Shongwe, Student Member, IEEE, Theo G. Swart, Member, IEEE, Hendrik C. Ferreira and Tran van Trung Abstract For communication schemes employing

More information

TIME encoding of a band-limited function,,

TIME encoding of a band-limited function,, 672 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II: EXPRESS BRIEFS, VOL. 53, NO. 8, AUGUST 2006 Time Encoding Machines With Multiplicative Coupling, Feedforward, and Feedback Aurel A. Lazar, Fellow, IEEE

More information

Three of these grids share a property that the other three do not. Can you find such a property? + mod

Three of these grids share a property that the other three do not. Can you find such a property? + mod PPMTC 22 Session 6: Mad Vet Puzzles Session 6: Mad Veterinarian Puzzles There is a collection of problems that have come to be known as "Mad Veterinarian Puzzles", for reasons which will soon become obvious.

More information

Multi-Radio Channel Detecting Jamming Attack Against Enhanced Jump-Stay Based Rendezvous in Cognitive Radio Networks

Multi-Radio Channel Detecting Jamming Attack Against Enhanced Jump-Stay Based Rendezvous in Cognitive Radio Networks Multi-Radio Channel Detecting Jamming Attack Against Enhanced Jump-Stay Based Rendezvous in Cognitive Radio Networks Yang Gao 1, Zhaoquan Gu 1, Qiang-Sheng Hua 2, Hai Jin 2 1 Institute for Interdisciplinary

More information

Permutation Tableaux and the Dashed Permutation Pattern 32 1

Permutation Tableaux and the Dashed Permutation Pattern 32 1 Permutation Tableaux and the Dashed Permutation Pattern William Y.C. Chen and Lewis H. Liu Center for Combinatorics, LPMC-TJKLC Nankai University, Tianjin, P.R. China chen@nankai.edu.cn, lewis@cfc.nankai.edu.cn

More information

The Classification of Quadratic Rook Polynomials of a Generalized Three Dimensional Board

The Classification of Quadratic Rook Polynomials of a Generalized Three Dimensional Board Global Journal of Pure and Applied Mathematics. ISSN 0973-1768 Volume 13, Number 3 (2017), pp. 1091-1101 Research India Publications http://www.ripublication.com The Classification of Quadratic Rook Polynomials

More information

((( ))) CS 19: Discrete Mathematics. Please feel free to ask questions! Getting into the mood. Pancakes With A Problem!

((( ))) CS 19: Discrete Mathematics. Please feel free to ask questions! Getting into the mood. Pancakes With A Problem! CS : Discrete Mathematics Professor Amit Chakrabarti Please feel free to ask questions! ((( ))) Teaching Assistants Chien-Chung Huang David Blinn http://www.cs cs.dartmouth.edu/~cs Getting into the mood

More information

Equivalence Classes of Permutations Modulo Replacements Between 123 and Two-Integer Patterns

Equivalence Classes of Permutations Modulo Replacements Between 123 and Two-Integer Patterns Equivalence Classes of Permutations Modulo Replacements Between 123 and Two-Integer Patterns Vahid Fazel-Rezai Phillips Exeter Academy Exeter, New Hampshire, U.S.A. vahid fazel@yahoo.com Submitted: Sep

More information

DEGRADED broadcast channels were first studied by

DEGRADED broadcast channels were first studied by 4296 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 54, NO 9, SEPTEMBER 2008 Optimal Transmission Strategy Explicit Capacity Region for Broadcast Z Channels Bike Xie, Student Member, IEEE, Miguel Griot,

More information

COUNTING AND PROBABILITY

COUNTING AND PROBABILITY CHAPTER 9 COUNTING AND PROBABILITY Copyright Cengage Learning. All rights reserved. SECTION 9.2 Possibility Trees and the Multiplication Rule Copyright Cengage Learning. All rights reserved. Possibility

More information

Closed Almost Knight s Tours on 2D and 3D Chessboards

Closed Almost Knight s Tours on 2D and 3D Chessboards Closed Almost Knight s Tours on 2D and 3D Chessboards Michael Firstein 1, Anja Fischer 2, and Philipp Hungerländer 1 1 Alpen-Adria-Universität Klagenfurt, Austria, michaelfir@edu.aau.at, philipp.hungerlaender@aau.at

More information

Permutation Groups. Every permutation can be written as a product of disjoint cycles. This factorization is unique up to the order of the factors.

Permutation Groups. Every permutation can be written as a product of disjoint cycles. This factorization is unique up to the order of the factors. Permutation Groups 5-9-2013 A permutation of a set X is a bijective function σ : X X The set of permutations S X of a set X forms a group under function composition The group of permutations of {1,2,,n}

More information

Lecture 2.3: Symmetric and alternating groups

Lecture 2.3: Symmetric and alternating groups Lecture 2.3: Symmetric and alternating groups Matthew Macauley Department of Mathematical Sciences Clemson University http://www.math.clemson.edu/~macaule/ Math 4120, Modern Algebra M. Macauley (Clemson)

More information

Problem 2A Consider 101 natural numbers not exceeding 200. Prove that at least one of them is divisible by another one.

Problem 2A Consider 101 natural numbers not exceeding 200. Prove that at least one of them is divisible by another one. 1. Problems from 2007 contest Problem 1A Do there exist 10 natural numbers such that none one of them is divisible by another one, and the square of any one of them is divisible by any other of the original

More information

Number Theory. Konkreetne Matemaatika

Number Theory. Konkreetne Matemaatika ITT9131 Number Theory Konkreetne Matemaatika Chapter Four Divisibility Primes Prime examples Factorial Factors Relative primality `MOD': the Congruence Relation Independent Residues Additional Applications

More information

Connected Identifying Codes

Connected Identifying Codes Connected Identifying Codes Niloofar Fazlollahi, David Starobinski and Ari Trachtenberg Dept. of Electrical and Computer Engineering Boston University, Boston, MA 02215 Email: {nfazl,staro,trachten}@bu.edu

More information

Deadlock-free Routing Scheme for Irregular Mesh Topology NoCs with Oversized Regions

Deadlock-free Routing Scheme for Irregular Mesh Topology NoCs with Oversized Regions JOURNAL OF COMPUTERS, VOL. 8, NO., JANUARY 7 Deadlock-free Routing Scheme for Irregular Mesh Topology NoCs with Oversized Regions Xinming Duan, Jigang Wu School of Computer Science and Software, Tianjin

More information

Olympiad Combinatorics. Pranav A. Sriram

Olympiad Combinatorics. Pranav A. Sriram Olympiad Combinatorics Pranav A. Sriram August 2014 Chapter 2: Algorithms - Part II 1 Copyright notices All USAMO and USA Team Selection Test problems in this chapter are copyrighted by the Mathematical

More information

An evolution of a permutation

An evolution of a permutation An evolution of a permutation Huseyin Acan April 28, 204 Joint work with Boris Pittel Notation and Definitions S n is the set of permutations of {,..., n} Notation and Definitions S n is the set of permutations

More information

Corners in Tree Like Tableaux

Corners in Tree Like Tableaux Corners in Tree Like Tableaux Pawe l Hitczenko Department of Mathematics Drexel University Philadelphia, PA, U.S.A. phitczenko@math.drexel.edu Amanda Lohss Department of Mathematics Drexel University Philadelphia,

More information

EXPLAINING THE SHAPE OF RSK

EXPLAINING THE SHAPE OF RSK EXPLAINING THE SHAPE OF RSK SIMON RUBINSTEIN-SALZEDO 1. Introduction There is an algorithm, due to Robinson, Schensted, and Knuth (henceforth RSK), that gives a bijection between permutations σ S n and

More information

What is counting? (how many ways of doing things) how many possible ways to choose 4 people from 10?

What is counting? (how many ways of doing things) how many possible ways to choose 4 people from 10? Chapter 5. Counting 5.1 The Basic of Counting What is counting? (how many ways of doing things) combinations: how many possible ways to choose 4 people from 10? how many license plates that start with

More information

Odd king tours on even chessboards

Odd king tours on even chessboards Odd king tours on even chessboards D. Joyner and M. Fourte, Department of Mathematics, U. S. Naval Academy, Annapolis, MD 21402 12-4-97 In this paper we show that there is no complete odd king tour on

More information

Gray code and loopless algorithm for the reflection group D n

Gray code and loopless algorithm for the reflection group D n PU.M.A. Vol. 17 (2006), No. 1 2, pp. 135 146 Gray code and loopless algorithm for the reflection group D n James Korsh Department of Computer Science Temple University and Seymour Lipschutz Department

More information

Permutation Groups. Definition and Notation

Permutation Groups. Definition and Notation 5 Permutation Groups Wigner s discovery about the electron permutation group was just the beginning. He and others found many similar applications and nowadays group theoretical methods especially those

More information

Fermat s little theorem. RSA.

Fermat s little theorem. RSA. .. Computing large numbers modulo n (a) In modulo arithmetic, you can always reduce a large number to its remainder a a rem n (mod n). (b) Addition, subtraction, and multiplication preserve congruence:

More information

Wilson s Theorem and Fermat s Theorem

Wilson s Theorem and Fermat s Theorem Wilson s Theorem and Fermat s Theorem 7-27-2006 Wilson s theorem says that p is prime if and only if (p 1)! = 1 (mod p). Fermat s theorem says that if p is prime and p a, then a p 1 = 1 (mod p). Wilson

More information

MAT3707. Tutorial letter 202/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/202/1/2017

MAT3707. Tutorial letter 202/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/202/1/2017 MAT3707/0//07 Tutorial letter 0//07 DISCRETE MATHEMATICS: COMBINATORICS MAT3707 Semester Department of Mathematical Sciences SOLUTIONS TO ASSIGNMENT 0 BARCODE Define tomorrow university of south africa

More information

A Graph Theory of Rook Placements

A Graph Theory of Rook Placements A Graph Theory of Rook Placements Kenneth Barrese December 4, 2018 arxiv:1812.00533v1 [math.co] 3 Dec 2018 Abstract Two boards are rook equivalent if they have the same number of non-attacking rook placements

More information

Heuristic Search with Pre-Computed Databases

Heuristic Search with Pre-Computed Databases Heuristic Search with Pre-Computed Databases Tsan-sheng Hsu tshsu@iis.sinica.edu.tw http://www.iis.sinica.edu.tw/~tshsu 1 Abstract Use pre-computed partial results to improve the efficiency of heuristic

More information