Browsing by Keywords "Hypergraph partitioning"
Now showing items 1-20 of 47
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Addressing volume and latency overheads in 1d-parallel sparse matrix-vector multiplication
(Springer, 2017-08-09)The scalability of sparse matrix-vector multiplication (SpMV) on distributed memory systems depends on multiple factors that involve different communication cost metrics. The irregular sparsity pattern of the coefficient ... -
Balance preserving min-cut replication set for a K-way hypergraph partitioning
(Bilkent University, 2010)Replication is a widely used technique in information retrieval and database systems for providing fault-tolerance and reducing parallelization and processing costs. Combinatorial models based on hypergraph partitioning ... -
Cache locality exploiting methods and models for sparse matrix-vector multiplication
(Bilkent University, 2009)The sparse matrix-vector multiplication (SpMxV) is an important kernel operation widely used in linear solvers. The same sparse matrix is multiplied by a dense vector repeatedly in these solvers to solve a system of ... -
Cartesian partitioning models for 2D and 3D parallel SpGEMM algorithms
(IEEE, 2020)The focus is distributed-memory parallelization of sparse-general-matrix-multiplication (SpGEMM). Parallel SpGEMM algorithms are classified under one-dimensional (1D), 2D, and 3D categories denoting the number of dimensions ... -
Clustering spatial networks for aggregate query processing: a hypergraph approach
(Elsevier Ltd, 2008-03)In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query processing. For this purpose, different techniques ... -
Decomposing linear programs for parallel solution
(Springer, 1995-08)Coarse grain parallelism inherent in the solution of Linear Programming (LP) problems with block angular constraint matrices has been exploited in recent research works. However, these approaches suffer from unscalability ... -
An effective model to decompose linear programs for parallel solution
(Springer, 1996-08)Although inherent parallelism in the solution of block angulax Linear Programming (LP) problems has been exploited in many research works, the literature that addresses decomposing constraint matrices into block angular ... -
Encapsulating multiple communication-cost metrics in partitioning sparse rectangular matrices for parallel matrix-vector multiplies
(SIAM, 2004)This paper addresses the problem of one-dimensional partitioning of structurally unsymmetric square and rectangular sparse matrices for parallel matrix-vector and matrix-transpose-vector multiplies. The objective is to ... -
Exploiting locality in sparse matrix-matrix multiplication on many-core rchitectures
(IEEE Computer Society, 2017)Exploiting spatial and temporal localities is investigated for efficient row-by-row parallelization of general sparse matrix-matrix multiplication (SpGEMM) operation of the form C=A,B on many-core architectures. Hypergraph ... -
Exploiting replicated data for communication load balancing in image-space parallel direct volume rendering of unstructured grids
(Bilkent University, 2009)The focus of this work is on parallel volume rendering applications in which renderings with different parameters are successively repeated over the same dataset. The only reason for inter-task interaction is the existence ... -
Hypergraph models for parallel sparse matrix-matrix multiplication
(Bilkent University, 2015-09)Multiplication of two sparse matrices (i.e., sparse matrix-matrix multiplication, which is abbreviated as SpGEMM) is a widely used kernel in many applications such as molecular dynamics simulations, graph operations, and ... -
Hypergraph partitioning and reordering for parallel sparse triangular solves and tensor decomposition
(Bilkent University, 2021-07)Several scientific and real-world problems require computations with sparse ma-trices, or more generally, sparse tensors which are multi-dimensional arrays. For sparse matrix computations, parallelization of sparse triangular ... -
A hypergraph partitioning model for profile minimization
(Society for Industrial and Applied Mathematics Publications, 2019)In this paper, the aim is to symmetrically permute the rows and columns of a given sparse symmetric matrix so that the profile of the permuted matrix is minimized. We formulate this permutation problem by first defining ... -
Hypergraph partitioning-based fill-reducing ordering for symmetric matrices
(Society for Industrial and Applied Mathematics, 2011)A typical first step of a direct solver for the lin ear system Mx = b is reordering of the symmetric matrix M to improve execution time and space requirements of the solution process. In this work, we propose a novel ... -
Hypergraph-partitioning-based decomposition for parallel sparse-matrix vector multiplication
(IEEE, 1999)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-vector multiplication. We propose two ... -
Hypergraph-partitioning-based remapping models for image-space-parallel direct volume rendering of unstructured grids
(Institute of Electrical and Electronics Engineers, 2007-07)In this work, image-space-parallel direct volume rendering (DVR) of unstructured grids is investigated for distributed-memory architectures. A hypergraph-partitioning-based model is proposed for the adaptive screen ... -
Improving medium-grain partitioning for scalable sparse tensor decomposition
(Institute of Electrical and Electronics Engineers, 2018)Tensor decomposition is widely used in the analysis of multi-dimensional data. The canonical polyadic decomposition (CPD) is one of the most popular decomposition methods and commonly found by the CPD-ALS algorithm. High ... -
Improving performance of sparse matrix dense matrix multiplication on large-scale parallel systems
(Elsevier BV, 2016)We propose a comprehensive and generic framework to minimize multiple and different volume-based communication cost metrics for sparse matrix dense matrix multiplication (SpMM). SpMM is an important kernel that finds ... -
Inverted index compression based on term and document identifier reassignment
(Bilkent University, 2008)Compression of inverted indexes received great attention in recent years. An inverted index consists of lists of document identifiers, also referred as posting lists, for each term. Compressing an inverted index reduces ... -
Investigation of load balancing scalability in space plasma simulations
(Springer, Berlin, Heidelberg, 2013)In this study we report the load-balancing performance issues that are observed during the petascaling of a space plasma simulation code developed at the Finnish Meteorological Institute (FMI). The code models the communication ...
