Browsing by Keywords "Sparse matrix-vector multiplication"
Now showing items 1-8 of 8
-
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 ... -
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. ... -
A novel method for scaling iterative solvers: avoiding latency overhead of parallel sparse-matrix vector multiplies
(Institute of Electrical and Electronics Engineers, 2015)In parallel linear iterative solvers, sparse matrix vector multiplication (SpMxV) incurs irregular point-to-point (P2P) communications, whereas inner product computations incur regular collective communications. These P2P ... -
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 ... -
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 latency cost in 2D sparse matrix partitioning models
(Elsevier BV, 2016)Sparse matrix partitioning is a common technique used for improving performance of parallel linear iterative solvers. Compared to solvers used for symmetric linear systems, solvers for nonsymmetric systems offer more ... -
Reordering methods for exploiting spatial and temporal localities in parallel sparse matrix-vector multiplication
(Bilkent University, 2016-08)Sparse Matrix-Vector multiplication (SpMV) is a very important kernel operation for many scientific applications. For irregular sparse matrices, the SpMV operation suffers from poor cache performance due to the irregular ... -
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 ...
