Browsing by Keywords "Sparse matrix"
Now showing items 1-9 of 9
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Hopping and correlation effects in atomic clusters and networks
(TechConnect, 2001)Exact solution for hopping and correlation effects in atomic clusters and mesoscopic/nanoscopic networks is outlined. The program translates the Hamiltonian operator of the cluster written in terms of second-quantized ... -
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 ... -
Locality-aware parallel sparse matrix-vector and matrix-transpose-vector multiplication on many-core processors
(Institute of Electrical and Electronics Engineers, 2016)Sparse matrix-vector and matrix-transpose-vector multiplication (SpMMTV) repeatedly performed as z ← ATx and y ← A z (or y ← A w) for the same sparse matrix A is a kernel operation widely used in various iterative solvers. ... -
Minimizing communication through computational redundancy in parallel iterative solvers
(Bilkent University, 2011)Sparse matrix vector multiplication (SpMxV) of the form y = Ax is a kernel operation in iterative linear solvers used in scientific applications. In these solvers, the SpMxV operation is performed repeatedly with the ... -
Optimizing nonzero-based sparse matrix partitioning models via reducing latency
(Academic Press, 2018)For the parallelization of sparse matrix-vector multiplication (SpMV) on distributed memory systems, nonzero-based fine-grain and medium-grain partitioning models attain the lowest communication volume and computational ... -
Parallel direct and hybrid methods based on row block partitioning for solving sparse linear systems
(Bilkent University, 2017-08)Solving system of linear equations is a kernel operation in many scienti c and industrial applications. These applications usually give rise to linear systems in which the coe cient matrix is very large and sparse. The ... -
Reduce operations: send volume balancing while minimizing latency
(IEEE, 2020)Communication hypergraph model was proposed in a two-phase setting for encapsulating multiple communication cost metrics (bandwidth and latency), which are proven to be important in parallelizing irregular applications. ... -
Reducing communication overhead in sparse matrix and tensor computations
(Bilkent University, 2020-08)Encapsulating multiple communication cost metrics, i.e., bandwidth and latency, is proven to be important in reducing communication overhead in the parallelization of sparse and irregular applications. Communication ... -
Spatiotemporal graph and hypergraph partitioning models for sparse matrix-vector multiplication on many-core architectures
(IEEE Computer Society, 2019)There exist graph/hypergraph partitioning-based row/column reordering methods for encoding either spatial or temporal locality for sparse matrix-vector multiplication (SpMV) operations. Spatial and temporal hypergraph ...
