Name
Abstract | ||
|---|---|---|
The matrix computations such as matrix-vector and matrix multiplication are very challenging computational kernels arising in scientific computing. In this paper, we study and evaluate a number of different data decomposition schemes for matrix computations on multicore architectures using OpenMP programming model. Further, in this work we propose a simple and fast analytical model to predict the performance of matrix computations by taking memory access costs into account and data access schemes that appear in many scientific applications. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/PDCAT.2010.52 | Parallel and Distributed Computing, Applications and Technologies |
Keywords | Field | DocType |
memory access cost,analytical model,different data,scientific application,scientific computing,matrix multiplication,matrix computations,performance models,computational kernel,data access scheme,openmp programming model,matrix computation,multicore,computational modeling,mathematical model,matrix decomposition,programming model,data access,multicore processors,multicore processing,synchronization | Synchronization,Programming paradigm,Computer science,Matrix (mathematics),Parallel computing,Matrix decomposition,Multi-core processor,Data access,Matrix multiplication,Computation | Conference |
ISBN | Citations | PageRank |
978-0-7695-4287-4 | 2 | 0.37 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Panagiotis D. Michailidis | 1 | 60 | 11.16 |
| Konstantinos G. Margaritis | 2 | 303 | 45.46 |