20916764
Low-complexity Interpolation Architecture for Soft-decision Reed-Solomon Decoding
Reed-Solomon (RS) codes have very broad applications in digital communication and storage systems. Among the decoding algorithms of RS codes, the Koetter-Vardy (KV) soft-decision decoding algorithm can achieve substantial coding gain with a polynomial complexity. One of the major steps of the KV algorithm is the interpolation. Recently, a new algorithm was proposed to solve the interpolation problem. Compared to previous efforts, this algorithm is computationally simpler, and thus can potentially lead to practical high-speed hardware implementations of the KV algorithm. This paper proposes novel transformation techniques to further reduce the hardware complexity of the new interpolation algorithm. In addition, efficient VLSI architectures are provided for the new algorithm
12946822
Partial parallel factorization in soft-decision Reed-Solomon decoding
Reed-Solomon (RS) codes have very broad applications in communications and data storage systems. The recently developed Koetter-Vardy (KV) soft-decision decoding algorithm of RS codes can achieve substantial coding gain, while has a complexity polynomial with respect to the codeword length. One of the major steps of the KV algorithm is the factorization step. A prediction-based architecture is developed in prior efforts to reduce the latency and silicon area of this step. However, the speedup can be achieved by this approach is limited by the serial nature of the factorization algorithm. The computations involved in multiple iteration levels can not be carried out simultaneously. In this work, a novel partial parallel architecture is proposed for the factorization step. The partial 2-parallel architecture can achieve a speedup of 19% over prior works.
8769201
Virtual workspaces: Achieving quality of service and quality of life in the Grid
By defining standardized protocols for discovering, accessing, monitoring, and managing remote computers, storage systems, networks, and other resources, Grid technologies make it possible—in principle—to allocate resources to applications dynamically, in an on-demand fashion [1]. However, while Grids offer users access to many diverse and powerful resources, they do little to ensure that once a resource is accessed, it fulfills user expectations for
10484270
Obligatory activator-polymerase addition order at promoters
The kinetics of open complex formation were measured by migration retardation assay and DNase I footprinting at the activator-dependent promoters ara P1, lac P1 and gal P1. In each case, the rate of open complex formation was significantly faster if the activator, AraC for ara and CAP for lac and gal, had been added before RNA polymerase. The results indicate that complexes of transcriptional activators, RNA polymerase and promoter can exist in two states, one which can form open complexes rapidly and one which cannot.
12113641
Neighbor number, valley seeking and clustering
This paper proposes a novel nonparametric clustering algorithm capable of identifying shape-free clusters. This algorithm is based on a nonparametric estimation of the normalized density derivative (NDD) and the local convexity of the density distribution function, both of which are represented in a very concise form in terms of neighbor numbers. We use NDD to measure the dissimilarity between each pair of observations in a local neighborhood and to build a connectivity graph. Combined with the local convexity, this similarity measure can detect observations in local minima (valleys) of the density function, which separate observations in different major clusters. We demonstrate that this algorithm has a close relationship with the single-linkage hierarchical clustering and can be viewed as its extension. The performance of the algorithm is tested with both synthetic and real datasets. An example of color image segmentation is also given. Comparisons with several representative existing algorithms show that the proposed method can robustly identify major clusters even when there are complex configurations and/or large overlaps.
8353152
An Efficient Algorithm for Mining Coherent Patterns from Heterogeneous Microarrays
DNA microarray techniques present a novel way for geneticists to monitor interactions among tens of thousands of genes simultaneously, and have become standard lab routines in gene discovery, disease diagnosis, and drug design. There has been extensive research on coherent subspace clustering of gene expressions measured under consistent experimental settings. This implies that all experiments are run using the same batch of microarray chips with similar characteristics of noise. Algorithms developed under this assumption may not be applicable for analyzing data collected from heterogeneous settings, where the set of genes being monitored may be different and expression levels may be not directly comparable even for the same gene. In this paper, we propose a model, F-cluster, for mining subspace coherent patterns from heterogeneous gene expression data, which is shown effective for revealing truthful patterns and reducing spurious ones. We also develop an efficient and scalable hybrid approach that combines gene-pair based and sample-pair based pruning to generate F-clusters from multiple gene expression matrices simultaneously. The experimental results demonstrate that our model can discover significant clusters that may not be identified by previous models.
5639888
Strategies for using additional resources in parallel hash-based join algorithms
Hash-based join is a compute- and memory-intensive algorithm. It achieves good performance and scales well to large datasets, if sufficient memory is available to hold the hash table and the distribution of computing had across nodes is balanced. We compare three adaptive algorithms that start with a partitioning of the hash table across a group of nodes and expand during the hash table building phase to additional resources, when memory on a node is used up. The split-based algorithm partitions the hash table range assigned to the node, on which memory is full, into two segments and assigns one of the segments to a new node in the system. The replication-based algorithm replicates the hash table range on a new node. The hybrid algorithm combines the first and second strategies in order to address each strategy's short comings. We perform an experimental performance evaluation of these algorithms on a PC cluster. Our results show that among the three algorithms, in most cases the hybrid algorithm either performs close to the better of the two or is the best algorithm.