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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
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Parallel hypergraph partitioning for scientific computing
Graph partitioning is often used for load balancing in parallel computing, but it is known that hypergraph partitioning has several advantages. First, hypergraphs more accurately model communicationExpand
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PaToH (Partitioning Tool for Hypergraphs)
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Benchmarking short sequence mapping tools
BackgroundThe development of next-generation sequencing instruments has led to the generation of millions of short sequences in a single run. The process of aligning these reads to a reference genomeExpand
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A comparative analysis of biclustering algorithms for gene expression data
The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discoverExpand
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A Scalable Distributed Parallel Breadth-First Search Algorithm on BlueGene/L
Many emerging large-scale data science applications require searching large graphs distributed across multiple memories and processors. This paper presents a distributed breadth- first search (BFS)Expand
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Permuting Sparse Rectangular Matrices into Block-Diagonal Form
We investigate the problem of permuting a sparse rectangular matrix into block-diagonal form. Block-diagonal form of a matrix grants an inherent parallelism for solving the deriving problem, asExpand
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Histopathological Image Analysis Using Model-Based Intermediate Representations and Color Texture: Follicular Lymphoma Grading
Follicular lymphoma (FL) is a cancer of lymph system and it is the second most common lymphoid malignancy in the western world. Currently, the risk stratification of FL relies on histological gradingExpand
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Graph coloring algorithms for multi-core and massively multithreaded architectures
We explore the interplay between architectures and algorithm design in the context of shared-memory platforms and a specific graph problem of central importance in scientific and high-performanceExpand
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Performance Evaluation of Sparse Matrix Multiplication Kernels on Intel Xeon Phi
Intel Xeon Phi is a recently released high-performance coprocessor which features 61 cores each supporting 4 hardware threads with 512-bit wide SIMD registers achieving a peak theoretical performanceExpand
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