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@@ -49,29 +49,42 @@ based on PSBLAS
-
Pasqua D'Ambra
+
Pasqua D'Ambra
+
IAC-CNR, Naples, Italy
+
+
+
+
Daniela di Serafino
+
University of Campania ``Luigi Vanvitelli'', Caserta, Italy
+
+
+
+
Salvatore Filippone
+
Cranfield University, Cranfield, United Kingdom
+
+
+
+
+
-ICAR-CNR, Naples, Italy
-
Daniela di Serafino
-Second University of Naples, Italy
-
Salvatore Filippone
-Cranfield University, United Kingdom
Software version: 2.1
-Feb. 28, 2017
+July 31, 2017
+
- + - +
+
-MLD2P4 has been designed to provide scalable and easy-to-use preconditioners +MLD2P4 has been designed to provide scalable and easy-to-use preconditioners in the context of the PSBLAS (Parallel Sparse Basic Linear Algebra Subprograms) computational framework and can be used in conjuction with the Krylov solvers available in this framework. MLD2P4 enables the user to easily specify different features of an algebraic multi-level preconditioner, thus allowing to search for the ``best'' preconditioner for the problem at hand. - +
-The package employs object-oriented design techniques in +The package employs object-oriented design techniques in Fortran 2003, with interfaces to additional third party libraries such as MUMPS, UMFPACK, SuperLU, and SuperLU_Dist, which can be exploited in building multi-level preconditioners. The parallel implementation is based on a Single Program Multiple Data (SPMD) paradigm; the inter-process communication is based on MPI and is managed mainly through PSBLAS. - +
-This guide provides a brief description of the functionalities and +This guide provides a brief description of the functionalities and the user interface of MLD2P4. +
- -
examples
and tests
directories;
both of them are further divided into fileread
and
pdegen
subdirectories. Their purpose is as follows:
-fileread
and
subdirectories, to experiment with the full range of preconditioners
implemented in the package.
fileread
directories contain sample programs that read
sparse matrices from files, according to the Matrix Market or the
Harwell-Boeing storage format; the pdegen
programs generate
matrices in full parallel mode from the discretization of a sample partial
differential equation.
+