35215015
Coarse Grain Preconditioned Conjugate Gradient Solver for Large Sparse Systems
We explore a coarse grain parallel algorithm for the solution of large sparse linear systems with symmetric positive definite matrix, based on a preconditioned conjugate gradient method.
5025109
Embedding Complete Binary Trees into Butterfly Networks
The authors present embeddings of complete binary trees into butterfly networks with or without wrap-around connections. Let m be an even integer and q=m+(log m)-1. The authors show how to embed a 2/sup q+1/-1-node complete binary tree T(q) into a (m+1)2/sup m+1/-node wrap-around butterfly B/sub w/(m+1) with a dilation of 4, and how to embed T(q) into a (m+2)2/sup m+2/-node wrap-around butterfly B/sub w/(m+2) with an optimal dilation of 2. They also present an embedding of a wrap-around butterfly B/sub w/(m) into a (m+1)2/sup m/-node no-wrap-around butterfly B(m) with a dilation of 3. Using this embedding it is shown that T(q) can be embedded into a no-wrap butterfly B(m+1) (resp. B(m+2)) with a dilation of 8 (resp. 5). >
195611449
Scheduling tasks in multiprocessor systems using evolutionary strategies
Scheduling tasks in multiprocessor systems is a difficult problem. The paper describes a method based upon evolutionary strategies (using genetic algorithms) to aid in finding good task assignments. The technique is illustrated by scheduling a digital signal processing algorithm on a two processor distributed system.<<ETX>>
715438
Non-linear Dimensionality Reduction by Locally Linear Isomaps
Algorithms for nonlinear dimensionality reduction (NLDR) find meaningful hidden low-dimensional structures in a high-dimensional space. Current algorithms for NLDR are Isomaps, Local Linear Embedding and Laplacian Eigenmaps. Isomaps are able to reliably recover low-dimensional nonlinear structures in high-dimensional data sets, but suffer from the problem of short-circuiting, which occurs when the neighborhood distance is larger than the distance between the folds in the manifolds. We propose a new variant of Isomap algorithm based on local linear properties of manifolds to increase its robustness to short-circuiting. We demonstrate that the proposed algorithm works better than Isomap algorithm for normal, noisy and sparse data sets.
8665183
Dynamic detection and removal of inactive clauses in SAT with application in image computation
In this paper, we present a new technique for the efficient dynamic detection and removal of inactive clauses, i.e. clauses that do not affect the solutions of interest of a Boolean satisfiability (SAT) problem. The algorithm is based on the extraction of gate connectivity information during generation of the Boolean formula from the circuit, and its use in the inner loop of a branch-and-bound SAT algorithm. The motivation for this optimization is to exploit the circuit structure information, which can be used to find unobservable gates at circuit outputs under dynamic conditions. It has the potential to speed up all applications of SAT in which the SAT formula is derived from a logic circuit. In particular, we find that it has considerable impact on an image computation algorithm based on SAT. We present practical results for benchmark circuits which show that the use of this optimization consistently improves the performance for reachability analysis, in some cases enabling the prototype tool to reach more states than otherwise possible.
18286724
Watermarking of MPEG-4 Videos
A MPEG-4 compressed domain video watermarking method is proposed and its performance is studied at video bit rates ranging from 64 Kb/s to 900 Kb/s. The watermark is inserted by modifying Discrete Cosine Transformation (DCT) coefficients. The strength of watermark is changed according to local frame characteristics to reduce impact on visual quality. The algorithm’s performance is also studied for watermarking bits in a frame ranging from 1 Kb/frame to 3 Kb/frame. The watermark is attack-free against attacks like scaling, rotation and cropping even if blind-techniques are used.
47205636
Approximation Algorithms for the Unsplittable Flow Problem
We present approximation algorithms for the unsplittable flow problem (UFP) on undirected graphs. As is standard in this line of research, we assume that the maximum demand is at most the minimum capacity. We focus on the non-uniform capacity case in which the edge capacities can vary arbitrarily over the graph. Our results are: - For undirected graphs we obtain a O(??-1 log2 n) approximation ratio, where n is the number of vertices, ? the maximum degree, and ? the expansion of the graph. Our ratio is capacity independent and improves upon the earlier O(??-1(cmax/cmin) log n) bound [15] for large values of cmax/cmin. Furthermore, if we specialize to the case where all edges have the same capacity, our algorithm gives an O(??-1 log n) approximation, which matches the performance of the best-known algorithm [15] for this special case. - For certain strong constant-degree expanders considered by Frieze [10] we obtain an O(? log n) approximation for the uniform capacity case, improving upon the current O(log n) approximation. - For UFP on the line and the ring, we give the first constant-factor approximation algorithms. Previous results addressed only the uniform capacity case. - All of the above results improve if the maximum demand is bounded away from the minimum capacity.Our results are based on randomized rounding followed by greedy alteration and are inspired by the use of this idea in recent work [21, 9].
14760800
Deciding Separation Logic Formulae by SAT and Incremental Negative Cycle Elimination
Separation logic is a subset of the quantifier-free first order logic. It has been successfully used in the automated verification of systems that have large (or unbounded) integer-valued state variables, such as pipelined processor designs and timed systems. In this paper, we present a fast decision procedure for separation logic, which combines Boolean satisfiability (SAT) with a graph based incremental negative cycle elimination algorithm. Our solver abstracts a separation logic formula into a Boolean formula by replacing each predicate with a Boolean variable. Transitivity constraints over predicates are detected from the constraint graph and added on a need-to basis. Our solver handles Boolean and theory conflicts uniformly at the Boolean level. The graph based algorithm supports not only incremental theory propagation, but also constant time theory backtracking without using a cumbersome history stack. Experimental results on a large set of benchmarks show that our new decision procedure is scalable, and outperforms existing techniques for this logic.