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Hypergraph-Partitioning-Based Decomposition for Parallel Sparse-Matrix Vector Multiplication
In this work, we show that the standard graph-partitioning-based decomposition of sparse matrices does not reflect the actual communication volume requirement for parallel matrix-vectorExpand
PaToH (Partitioning Tool for Hypergraphs)
Parallel hypergraph partitioning for scientific computing
This work presents a parallel software package for hypergraph (and sparse matrix) partitioning developed at Sandia National Labs, and presents empirical results that show the parallel implementation achieves good speedup on several large problems. Expand
Benchmarking short sequence mapping tools
A benchmarking suite to extensively analyze sequencing tools with respect to various aspects and provide an objective comparison is provided that reveals and evaluates the different factors affecting the mapping process. Expand
A Scalable Distributed Parallel Breadth-First Search Algorithm on BlueGene/L
This paper presents a distributed breadth- first search (BFS) scheme that scales for random graphs with up to three billion vertices and 30 billion edges, and develops efficient collective communication functions for the 3D torus architecture of BlueGene/L that take advantage of the structure in the problem. Expand
Graph coloring algorithms for multi-core and massively multithreaded architectures
Two different kinds of multithreaded heuristic algorithms for the stated, NP-hard, graph coloring problem are introduced and shown to have scalable runtime performance and use nearly the same number of colors as the underlying serial algorithm, which in turn is effective in practice. Expand
A comparative analysis of biclustering algorithms for gene expression data
The analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise, and these algorithms are observed to be more successful at capturing biologically relevant clusters. Expand
Streaming Algorithms for k-core Decomposition
This paper proposes the first incremental k-core decomposition algorithms for streaming graph data, which locate a small subgraph that is guaranteed to contain the list of vertices whose maximum k-Core values have to be updated, and efficiently process this subgraph to update the k- core decomposition. Expand
Permuting Sparse Rectangular Matrices into Block-Diagonal Form
To represent the nonzero structure of a matrix, bipartite graph and hypergraph models that reduce the permutation problem to those of graph partitioning by vertex separator andhypergraph partitioning, respectively are proposed. Expand
Histopathological Image Analysis Using Model-Based Intermediate Representations and Color Texture: Follicular Lymphoma Grading
A model-based intermediate representation of cytological components that enables higher level semantic description of tissue characteristics and a novel color-texture analysis approach that combines the MBIR with low level texture features, which capture tissue characteristics at pixel level are introduced. Expand