Application of hash to data base machine and its architecture

In this paper we discuss the application of the dynamic clustering feature of hash to a relational data base machine. By partitioning the relation using hash, large load reductions in join and set operations are realized. Several machine architectures based on hash are presented. We propose a data base machineGRACE which adopts a novel relational algebraic processing algorithm based on hash and sort. Whereas conventional logic-per-track machines perform poorly in a join dominant environment,GRACE can execute join efficiently inO(N+M/K) time, whereN andM are the cardinalities of two relations andK the number of memory banks.     

Analysis of Multi-Sort Algorithm on Multi-Mesh of Trees (MMT) architecture

Various sorting algorithms using parallel architectures have been proposed in the search for more efficient results. This paper introduces the Multi-Sort Algorithm for Multi-Mesh of Trees (MMT) Architecture for N=n ⁴ elements with more efficient time complexity compared to previous architectures. The shear sort algorithm on Single Instruction Multiple Data (SIMD) mesh model requires \(4\sqrt{N}+O\sqrt{N}\) time for sorting N elements, arranged on a \(\sqrt{N}\times \sqrt{N}\) mesh, whereas Multi-Sort algorithm on the SIMD Multi-Mesh (MM) Architecture takes O(N ^1/4) time for sorting the same N elements, which proves that Multi-Sort is a better sorting approach. We have improved the time complexity of intrablock Sort. The Communication time complexity for 2D Sort in MM is O(n), whereas this time in MMT is O(log?n). The time complexity of compare–exchange step in MMT is same as that in MM, i.e., O(n). It has been found that the time complexity of the Multi-Sort on MMT has been improved as on Multi-Mesh architecture.     

An SDP Primal-Dual Algorithm for Approximating the Lovász-Theta Function

The Lovász ?-function (Lovász in IEEE Trans. Inf. Theory, 25:1–7, 1979) of a graph G=(V,E) can be defined as the maximum of the sum of the entries of a positive semidefinite matrix X, whose trace Tr(X) equals 1, and X _ij =0 whenever {i,j}∈E. This function appears as a subroutine for many algorithms for graph problems such as maximum independent set and maximum clique. We apply Arora and Kale’s primal-dual method for SDP to design an algorithm to approximate the ?-function within an additive error of δ>0, which runs in time $O(\frac{\vartheta ^{2} n^{2}}{\delta^{2}} \log n \cdot M_{e})$ , where ?=?(G) and M _e =O(n ³) is the time for a matrix exponentiation operation. It follows that for perfect graphs G, our primal-dual method computes ?(G) exactly in time O(? ² n ⁵logn). Moreover, our techniques generalize to the weighted Lovász ?-function, and both the maximum independent set weight and the maximum clique weight for vertex weighted perfect graphs can be approximated within a factor of (1+?) in time O(? ^?2 n ⁵logn).     

Minimum Manhattan Network Problem in Normed Planes with Polygonal Balls: A Factor 2.5 Approximation Algorithm

Let ${\mathcal{B}}$ be a centrally symmetric convex polygon of ?² and ‖p?q‖ be the distance between two points p,q∈?² in the normed plane whose unit ball is ${\mathcal{B}}$ . For a set T of n points (terminals) in ?², a ${\mathcal{B}}$ -network on T is a network N(T)=(V,E) with the property that its edges are parallel to the directions of ${\mathcal{B}}$ and for every pair of terminals t _i and t _j , the network N(T) contains a shortest ${\mathcal{B}}$ -path between them, i.e., a path of length ‖t _i ?t _j ‖. A minimum ${\mathcal{B}}$ -network on T is a ${\mathcal{B}}$ -network of minimum possible length. The problem of finding minimum ${\mathcal{B}}$ -networks has been introduced by Gudmundsson, Levcopoulos, and Narasimhan (APPROX’99) in the case when the unit ball ${\mathcal{B}}$ is a square (and hence the distance ‖p?q‖ is the l ₁ or the l _∞-distance between p and q) and it has been shown recently by Chin, Guo, and Sun (Symposium on Computational Geometry, pp. 393–402, 2009) to be strongly NP-complete. Several approximation algorithms (with factors 8, 4, 3, and 2) for the minimum Manhattan problem are known. In this paper, we propose a factor 2.5 approximation algorithm for the minimum ${\mathcal{B}}$ -network problem. The algorithm employs a simplified version of the strip-staircase decomposition proposed in our paper (Chepoi et al. in Theor. Comput. Sci. 390:56–69, 2008, and APPROX-RANDOM, pp. 40–51, 2005) and subsequently used in other factor 2 approximation algorithms for the minimum Manhattan problem.     

Solving visibility and separability problems on a mesh-of-processors

In this paper we study parallel algorithms for the Mesh-of-Processors architecture to solve visibility and related separability problems for sets of simple polygons in the plane. In particular, we present the following algorithms:

- AnO( \(\sqrt N\) time algorithm for computing on a Mesh-of-Processors of size N the visibility polygon from a point located in anN-vertex polygon, possibly with holes.

-O( \(\sqrt N\) ) time algorithms for computing on a Mesh-of-Processors of sizeN the set of all points on the boundary of anN-vertex polygonP which are visible in a given directiond as well as the visibility hull ofP for a given directiond.

- AnO( \(\sqrt N\) ) time algorithm for detecting on a Mesh-of-Processors of size 2N whether twoN-vertex polygons are separable in a given direction and anO( \(\sqrt {MN}\) ) time algorithm for detecting on a Mesh-of-Processors of sizeMN whetherM N-vertex polygons are sequentially separable in a given direction.

All proposed algorithms are asymptotically optimal (for the Mesh-of-Processors) with respect to time and number of processors.     

An optimal arc consistency algorithm for a particular case of sequence constraint

The AtMostSeqCard constraint is the conjunction of a cardinality constraint on a sequence of n variables and of n???q?+?1 constraints AtMost u on each subsequence of size q. This constraint is useful in car-sequencing and crew-rostering problems. In van Hoeve et al. (Constraints 14(2):273–292, 2009), two algorithms designed for the AmongSeq constraint were adapted to this constraint with an O(2 ^q n) and O(n ³) worst case time complexity, respectively. In Maher et al. (2008), another algorithm similarly adaptable to filter the AtMostSeqCard constraint with a time complexity of O(n ²) was proposed. In this paper, we introduce an algorithm for achieving arc consistency on the AtMostSeqCard constraint with an O(n) (hence optimal) worst case time complexity. Next, we show that this algorithm can be easily modified to achieve arc consistency on some extensions of this constraint. In particular, the conjunction of a set of m AtMostSeqCard constraints sharing the same scope can be filtered in O(nm). We then empirically study the efficiency of our propagator on instances of the car-sequencing and crew-rostering problems.     

Local noncuppability in R/M

Given any [c], [a], [d] xxxxxxxxR/M such that [d] ≤ [a] ≤ [c], [a] is locally noncuppable between [c] and [d] if [d] < [a] ≤ [c] and [a] ∨ [b] < [c] for any [b] xxxxxxxxR/M such that [d] ≤ [b] < [c]. It will be shown that given any nonzero [c] xxxxxxxxR/M, there are [a], [d] xxxxxxxxR/M such that [d] < [a] ≤ [c] and [a] is locally noncuppable between [c] and [d].     

Nearly-Linear Work Parallel SDD Solvers,Low-Diameter Decomposition,and Low-Stretch Subgraphs

We present the design and analysis of a nearly-linear work parallel algorithm for solving symmetric diagonally dominant (SDD) linear systems. On input an SDD n-by-n matrix A with m nonzero entries and a vector b, our algorithm computes a vector \(\tilde{x}\) such that \(\|\tilde{x} - A^{+}b\|_{A} \leq\varepsilon\cdot\|{A^{+}b}\|_{A}\) in \(O(m\log^{O(1)}{n}\log {\frac{1}{\varepsilon}})\) work and \(O(m^{1/3+\theta}\log\frac{1}{\varepsilon})\) depth for any θ>0, where A ⁺ denotes the Moore-Penrose pseudoinverse of A. The algorithm relies on a parallel algorithm for generating low-stretch spanning trees or spanning subgraphs. To this end, we first develop a parallel decomposition algorithm that in O(mlog ^O(1) n) work and polylogarithmic depth, partitions a graph with n nodes and m edges into components with polylogarithmic diameter such that only a small fraction of the original edges are between the components. This can be used to generate low-stretch spanning trees with average stretch O(n ^α ) in O(mlog ^O(1) n) work and O(n ^α ) depth for any α>0. Alternatively, it can be used to generate spanning subgraphs with polylogarithmic average stretch in O(mlog ^O(1) n) work and polylogarithmic depth. We apply this subgraph construction to derive a parallel linear solver. By using this solver in known applications, our results imply improved parallel randomized algorithms for several problems, including single-source shortest paths, maximum flow, minimum-cost flow, and approximate maximum flow.     

A Polynomial-Time Approximation Algorithm for One Problem Simulating the Search in a Time Series for the Largest Subsequence of Similar Elements

We analyze the mathematical aspects of the data analysis problem consisting in the search (selection) for a subset of similar elements in a group of objects. The problem arises, in particular, in connection with the analysis of data in the form of time series (discrete signals). One of the problems in modeling this challenge is considered, namely, the problem of searching in a finite sequence of points from the Euclidean space for the subsequence with the greatest number of terms such that the quadratic spread of the elements of this subsequence with respect to its unknown centroid does not exceed a given percentage of the quadratic spread of elements of the input sequence with respect to its centroid. It is shown that the problem is strongly NP-hard. A polynomial-time approximation algorithm is proposed. This algorithm either establishes that the problem has no solution or finds a 1/2-approximate solution if the length M^* of the optimal subsequence is even, or it yields a \(\frac{1}{2}\left(\begin{array}{c}1-\frac{1}{M^*}\\ \end{array}\right)\)-approximate solution if M* is odd. The time complexity of the algorithm is O(N³(N²+q)), where N is the number of points in the input sequence and q is the space dimension. The results of numerical simulation that demonstrate the effectiveness of the algorithm are presented.     

Random arithmetic formulas can be reconstructed efficiently

Informally stated, we present here a randomized algorithm that given black-box access to the polynomial f computed by an unknown/hidden arithmetic formula ? reconstructs, on the average, an equivalent or smaller formula \({\hat{\phi}}\) in time polynomial in the size of its output \({\hat{\phi}}\) . Specifically, we consider arithmetic formulas wherein the underlying tree is a complete binary tree, the leaf nodes are labeled by affine forms (i.e., degree one polynomials) over the input variables and where the internal nodes consist of alternating layers of addition and multiplication gates. We call these alternating normal form (ANF) formulas. If a polynomial f can be computed by an arithmetic formula μ of size s, it can also be computed by an ANF formula ?, possibly of slightly larger size s ^O(1). Our algorithm gets as input black-box access to the output polynomial f (i.e., for any point x in the domain, it can query the black box and obtain f(x) in one step) of a random ANF formula ? of size s (wherein the coefficients of the affine forms in the leaf nodes of ? are chosen independently and uniformly at random from a large enough subset of the underlying field). With high probability (over the choice of coefficients in the leaf nodes), the algorithm efficiently (i.e., in time s ^O(1)) computes an ANF formula \({\hat{\phi}}\) of size s computing f. This then is the strongest model of arithmetic computation for which a reconstruction algorithm is presently known, albeit efficient in a distributional sense rather than in the worst case.     

PP-Lowness and a Simple Definition of AWPP

Abstract. We show that the counting classes AWPP and APP [FFKL], [L] are more robust than previously thought. Our results identify a sufficient condition for a language to be low for PP, and we show that this condition is at least as weak as other previously studied criteria. We extend a result of Köbler et al. by proving that all sparse co-C ₌ P languages are in APP, and are thus PP-low. Our results also imply that AWPP ?eq APP, and thus APP contains many other established subclasses of PP-low, thereby reducing several different lowness results to membership in APP. We also show that AWPP and APP are Σ ⁰ ₂ -definable classes. Some of our results are reminiscent of amplifying certainty in probabilistic computation.     

Parallel geometric hashing for robust iris indexing

In this paper an effort has been made to improve the time complexity of existing geometric hashing based indexing approach for iris biometrics [1]. In the conventional approach, the annular iris image is used for the extraction of keypoints using Scale Invariant Feature Transform [2]. Further, geometric hashing [3] is used to index the database using extracted keypoints. The existing approach performs with an accuracy of 98.5% with improvement in time. However, to further improve time complexity, existing geometric hashing approach is made parallel during indexing as well as retrieval phase. In the proposed approach, the extracted keypoints are mapped to the processors of the hypercube through shared global memory. The geometric invariants are obtained for each basis pair allotted to individual processors in parallel. During indexing phase, these invariants are stored in the hash table. For iris retrieval, the invariants are obtained and the corresponding entries in the hash table receive a vote. The time complexity of the proposed approach is O(Mn ²) for M iris images each having n keypoints, in comparison to existing approach with time complexity of O(Mn ³). This marks the suitability of proposed approach for real-time applications.     

Contracting Graphs to Paths and Trees

Vertex deletion and edge deletion problems play a central role in parameterized complexity. Examples include classical problems like Feedback Vertex Set, Odd Cycle Transversal, and Chordal Deletion. The study of analogous edge contraction problems has so far been left largely unexplored from a parameterized perspective. We consider two basic problems of this type: Tree Contraction and Path Contraction. These two problems take as input an undirected graph G on n vertices and an integer k, and the task is to determine whether we can obtain a tree or a path, respectively, by a sequence of at most k edge contractions in G. For Tree Contraction, we present a randomized 4 ^k ? n ^O(1) time polynomial-space algorithm, as well as a deterministic 4.98 ^k ? n ^O(1) time algorithm, based on a variant of the color coding technique of Alon, Yuster and Zwick. We also present a deterministic 2 ^k+o(k)+n ^O(1) time algorithm for Path Contraction. Furthermore, we show that Path Contraction has a kernel with at most 5k+3 vertices, while Tree Contraction does not have a polynomial kernel unless NP ? coNP/poly. We find the latter result surprising because of the connection between Tree Contraction and Feedback Vertex Set, which is known to have a kernel with 4k ² vertices.     

On Cutwidth Parameterized by Vertex Cover

We study the Cutwidth problem, where the input is a graph G, and the objective is find a linear layout of the vertices that minimizes the maximum number of edges intersected by any vertical line inserted between two consecutive vertices. We give an algorithm for Cutwidth with running time O(2 ^k n ^O(1)). Here k is the size of a minimum vertex cover of the input graph G, and n is the number of vertices in G. Our algorithm gives an O(2 ^n/2 n ^O(1)) time algorithm for Cutwidth on bipartite graphs as a corollary. This is the first non-trivial exact exponential time algorithm for Cutwidth on a graph class where the problem remains NP-complete. Additionally, we show that Cutwidth parameterized by the size of the minimum vertex cover of the input graph does not admit a polynomial kernel unless NP?coNP/poly. Our kernelization lower bound contrasts with the recent results of Bodlaender et al. (ICALP, Springer, Berlin, 2011; SWAT, Springer, Berlin, 2012) that both Treewidth and Pathwidth parameterized by vertex cover do admit polynomial kernels.     

A Quantum Characterization Of NP

In this article, we introduce a new complexity class called PQMA _log(2). Informally, this is the class of languages for which membership has a logarithmic-size quantum proof with perfect completeness and soundness, which is polynomially close to 1 in a context where the verifier is provided a proof with two unentangled parts. We then show that PQMA _log(2) =? NP. For this to be possible, it is important, when defining the class, not to give too much power to the verifier. This result, when compared to the fact that QMA _log =? BQP, gives us new insight into the power of quantum information and the impact of entanglement.     

Query-Efficient Locally Decodable Codes of Subexponential Length

A k-query locally decodable code (LDC) C : Σ ⁿ → Γ ^N encodes each message x into a codeword C(x) such that each symbol of x can be probabilistically recovered by querying only k coordinates of C(x), even after a constant fraction of the coordinates has been corrupted. Yekhanin (in J ACM 55:1–16, 2008) constructed a 3-query LDC of subexponential length, N = exp(exp(O(log n/log log n))), under the assumption that there are infinitely many Mersenne primes. Efremenko (in Proceedings of the 41st annual ACM symposium on theory of computing, ACM, New York, 2009) constructed a 3-query LDC of length ${N_{2}={\rm exp}({\rm exp} (O(\sqrt{\log n\log\log n})))}$ with no assumption, and a 2 ^r -query LDC of length ${N_{r}={\rm exp}({\rm exp}(O(\sqrt[r]{\log n(\log \log n)^{r-1}})))}$ , for every integer r ≥ 2. Itoh and Suzuki (in IEICE Trans Inform Syst E93-D 2:263–270, 2010) gave a composition method in Efremenko’s framework and constructed a 3 · 2 ^r-2-query LDC of length N _r , for every integer r ≥ 4, which improved the query complexity of Efremenko’s LDC of the same length by a factor of 3/4. The main ingredient of Efremenko’s construction is the Grolmusz construction for super-polynomial size set-systems with restricted intersections, over ${\mathbb{Z}_m}$ , where m possesses a certain “good” algebraic property (related to the “algebraic niceness” property of Yekhanin in J ACM 55:1–16, 2008). Efremenko constructed a 3-query LDC based on m = 511 and left as an open problem to find other numbers that offer the same property for LDC constructions. In this paper, we develop the algebraic theory behind the constructions of Yekhanin (in J ACM 55:1–16, 2008) and Efremenko (in Proceedings of the 41st annual ACM symposium on theory of computing, ACM, New York, 2009), in an attempt to understand the “algebraic niceness” phenomenon in ${\mathbb{Z}_m}$ . We show that every integer m =  pq = 2 ^t ?1, where p, q, and t are prime, possesses the same good algebraic property as m = 511 that allows savings in query complexity. We identify 50 numbers of this form by computer search, which together with 511, are then applied to gain improvements on query complexity via Itoh and Suzuki’s composition method. More precisely, we construct a ${3^{\lceil r/2\rceil}}$ -query LDC for every positive integer r < 104 and a ${\left\lfloor (3/4)^{51} \cdot 2^{r}\right\rfloor}$ -query LDC for every integer r ≥ 104, both of length N _r , improving the 2 ^r queries used by Efremenko (in Proceedings of the 41st annual ACM symposium on theory of computing, ACM, New York, 2009) and 3 · 2 ^r-2 queries used by Itoh and Suzuki (in IEICE Trans Inform Syst E93-D 2:263–270, 2010). We also obtain new efficient private information retrieval (PIR) schemes from the new query-efficient LDCs.     

ALTEP — A cellular processor for high-speed pattern matching

The design of a high-speed cellular pattern matcher, called theAssociative Linear Text Processor (ALTEP), is presented.ALTEP was originally designed for systems which use signature files as an access method. However, it is also suitable for systems which store the database in fixed length blocks.ALTEP is a linear array of logic cells which respond to commands sent from a central controller over a bus. A text block is loaded into the cells and pattern characters are broadcast to the cells for comparison.ALTEP has the capability of recognizing full regular expressions and is the only cellular logic array which has this capability. It requiresO(p) steps for patterns which do not contain closures andO(len(max(T(P)))) steps for closures, wherep is the the length of the pattern andlen(max(T(P))) is the length of the longest substring in the text which matched the closure.     

The amplified quantum Fourier transform: solving the local period problem

This paper creates and analyzes a new quantum algorithm called the Amplified Quantum Fourier Transform (QFT) for solving the following problem: The Local Period Problem: Let L = {0,1 . . . N?1} be a set of N labels and let A be a subset of M labels of period P, i.e. a subset of the form $$A=\{j:j=s+rP,r=0,1\ldots M-1\}$$ where ${P\leq \sqrt{N}}$ and ${M \ll N}$ , and where M is assumed known. Given an oracle f : L→ {0,1} which is 1 on A and 0 elsewhere, find the local period P and the offset s. The first part of this paper defines the Amplified QFT algorithm. The second part of the paper summarizes the main results and compares the new algorithm against the QFT and QHS algorithms when solving the local period problem. It is shown that the new algorithm is, on average, quadratically faster than both the QFT and QHS algorithms.     

The M-computations induced by accessibility relations in nonstandard models M of Hoare logic

Hoare logic [1] is a logic used as a way of specifying semantics of programming languages, which has been extended to be a separation logic to reason about mutable heap structure [2]. In a model M of Hoare logic, each program α induces an M-computable function f _α ^M on the universe of M; and the M-recursive functions are defined on M. It will be proved that the class of all the M-computable functions f _α ^M induced by programs is equal to the class of all the M-recursive functions. Moreover, each M-recursive function is \(\sum {_1^{{N^M}}} \)-definable in M, where the universal quantifier is a number quantifier ranging over the standard part of a nonstandard model M.     

A note on balanced immunity

For a finite alphabet ∑ we define a binary relation on \(2^{\Sigma *} \times 2^{2^{\Sigma ^* } } \) , called balanced immunity. A setB ? ∑* is said to be balancedC-immune (with respect to a classC ? 2^Σ* of sets) iff, for all infiniteL εC, $$\mathop {\lim }\limits_{n \to \infty } \left| {L^{ \leqslant n} \cap B} \right|/\left| {L^{ \leqslant n} } \right| = \tfrac{1}{2}$$ Balanced immunity implies bi-immunity and in natural cases randomness. We give a general method to find a balanced immune set'B for any countable classC and prove that, fors(n) =o(t(n)) andt(n) >n, there is aB εSPACE(t(n)), which is balanced immune forSPACE(s(n)), both in the deterministic and nondeterministic case.