22669962
Generic universal switch blocks
A switch block M with W terminals on each side is said to be universal if every set of nets satisfying the dimension constraint (i.e., the number of nets on each side of M is at most W) is simultaneously routable through M (Y.W. Chang et al., 1996). We present an algorithm to construct N-sided universal switch blocks with W terminals on each side. Each of our universal switch blocks has (/sub 2//sup N/)W switches and switch-block flexibility N-1 (i.e., F/sub S/=N-1). We prove that no switch block with less than (/sub 2//sup N/)W switches can be universal. Further, the decomposition property of a universal switch block provides a key insight into its layout implementation with a smaller silicon area. We also compare our universal switch blocks with others of the topology associated with Xilinx XC4000-type FPGAs. Experimental results demonstrate that our universal switch blocks improve routability at the chip level.
6594297
Generic Universal Switch Blocks
A switch block M with W terminals on each side is said to be universal if every set of nets satisfying the dimension constraint (i.e., the number of nets on each side of M is at most W) is simultaneously routable through M. In this paper, we present an algorithm to construct N-sided universal switch blocks with W terminals on each side. Each of our universal switch blocks has (/sub 2//sup N/) W switches and switch-block flexibility N-1 (i.e., F/sub S/=N-1). We prove that no switch block with less than (/sub 2//sup N/)W switches can be universal. We also compare our universal switch blocks with others of the topology associated with Xilinx XC4000-type FPGAs. To explore the area performance of the universal switch blocks, we develop a detailed router for hierarchical FPGAs (HFPGAs) with 5-sided switch blocks. Experimental results demonstrate that our universal switch blocks improve routability at the chip level. Based on extensive experiments, we also provide key insights into the interactions between switch-block architectures and routing.
13757062
Faster solution to the maximum quartet consistency problem with constraint programming
Evolution is an important sub-area of study in biological science, whereby the evolutionary history, or phylogeny, would shed light on the genetic linkage and the functional correlation for the species under consideration. Many kinds of species data can be deployed for the task and many phylogeny reconstruction methods have been examined in the literature. A quartet approach is to build a local phylogeny for every 4 species, which is called a quartet for these 4 species, and then to assemble a phylogeny for the whole set of species satisfying the topological constraints imposed by these quartets built. In practice, those predicted quartets might not agree each other and the optimization problem, the well-known Maximum Quartet Consistency (MQC) problem, is to construct a phylogeny to satisfy a maximum number of the predicted quartets. An equivalent representation for the MQC problem through searching for a certain ultrametric matrix via Answer Set Programming has recently been proposed. This paper follows the approach and presents a number of optimization techniques to speed up the searching process. The experimental results on both the simulated and real datasets suggest that the new representation combined with Constraint Programming presents a unique perspective to the MQC problem.
16585637
Learning with non-metric proximity matrices
Many emerging applications formulate non-metric proximity matrices (non-positive semidefinite), and hence cannot fit into the framework of kernel machines. A popular approach to this problem is to transform the spectrum of the similarity matrix so as to generate a positive semidefinite kernel matrix. In this paper, we explore four representative transformation methods: denoise, flip, diffusion, and shift. Theoretically, we discuss a generalization problem where the test data are not available during transformation, and thus propose an efficient algorithm to address the problem of updating the cross-similarity matrix between test and training data. Extensive experiments have been conducted to evaluate the performance of these methods on several real-world (dis)similarity matrices with semantic meanings.
5979296
A Lookahead Branch-and-Bound Algorithm for the Maximum Quartet Consistency Problem
A lookahead branch-and-bound algorithm (LBnB) is proposed for solving the Maximum Quartet Consistency (MQC) Problem where the input is a complete set of quartets on the taxa and the goal is to construct a phylogeny that satisfies the maximum number of given quartets. It integrates a number of previous efforts on exact algorithms, heuristics, and approximation algorithms for the NP-hard MQC problem, and a few improved search techniques, especially a lookahead scheme, to solve the problem optimally. The theoretical running time analysis of the LBnB algorithm is provided, and an extensive simulation study has been well designed to compare the algorithm to previous existing exact algorithms and a best heuristic Hypercleaning. The experimental results on both synthetic and real datasets show that LBnB outperformed other exact algorithms, and it was competitive to Hypercleaning on many datasets.
7723209
1-Generic splittings of computably enumerable degrees
Say a set G⊆ω is 1-generic if for any e∈ω, there is a string σ⊂G such that {e}σ(e)↓ or ∀τ⊇σ({e}τ(e)↑). It is known that 0′ can be split into two 1-generic degrees. In this paper, we generalize this and prove that any nonzero computably enumerable degree can be split into two 1-generic degrees. As a corollary, no two computably enumerable degrees bound the same class of 1-generic degrees.
2388375
Congestion control via online sampling
We consider the congestion control problem in a communication network with multiple traffic sources, each modeled as a fully-controllable stream of fluid traffic. The controlled traffic shares a common bottleneck node with high-priority cross traffic described by a Markov-modulated fluid (MMF). Each controlled source is assumed to have a unique round-trip delay. We wish to maximize a linear combination of the throughput, delay, traffic loss rate, and a fairness metric at the bottleneck node. We introduce an online sampling-based burst-level congestion control scheme capable of performing effectively under rapidly-varying cross traffic by making explicit use of the provided MMF model of that variation. The control problem is posed as a finite-horizon Markov decision process and is solved heuristically using a technique called hindsight optimization. We provide a detailed derivation of our congestion control algorithm based on this technique. The distinguishing feature of our scheme relative to conventional congestion control schemes is that we exploit a stochastic model of the cross traffic. Our empirical study shows that our control scheme significantly outperforms the conventional proportional-derivative (PD) controller, achieving higher utilization, lower delay, and lower loss under reasonable fairness. The performance advantage of our scheme over the PD scheme grows as the rate variance of cross traffic increases, underscoring the effectiveness of our control scheme under variable cross traffic.