Download Advances in Software Tools for Scientific Computing by Jeremy Siek, Andrew Lumsdaine (auth.), Hans Petter PDF

By Jeremy Siek, Andrew Lumsdaine (auth.), Hans Petter Langtangen, Are Magnus Bruaset, Ewald Quak (eds.)

To make complete use of the ever expanding services of contemporary com­ puters, it can be crucial to quickly improve the functionality and reliability of the software program in addition, and sometimes with no need an appropriate mathematical conception on hand. within the dealing with of progressively more complicated real-life numerical difficulties in all kinds of purposes, a contemporary object-oriented de­ signal and implementation of software program instruments has turn into a very important part. The significant demanding situations posed through the call for for effective object-oriented software program in all components of medical computing make it essential to alternate rules and studies from as many alternative resources as attainable. inspired via the luck of the 1st assembly of this type in Norway in 1996, we made up our minds to arrange one other foreign Workshop on smooth software program instruments for medical Computing, also known as SciTools'98. This workshop happened in Oslo, Norway, September 14-16, 1998. The ob­ jective was once back to supply an open discussion board for trade and dialogue of recent, state of the art software program thoughts utilized to not easy numerical difficulties. The association used to be undertaken together by means of the examine institute SINTEF utilized arithmetic, the Departments of arithmetic and Infor­ matics on the college of Oslo, and the corporate Numerical gadgets AS.

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We would like to broaden the number of matrix types supported in the MTL, including diagonally oriented matrices, Hermitian matrices, hierarchical matrices, and various types of blocked (super-node) sparse matrices. In addition, we will continue to add numerical types that can be used with MTL, such as intervals and variable precision (an extended precision class is currently distributed with MTL). Some of the algorithms in MTL need further optimization, especially in the area of sparse matrix operations.

For the packed case, the beginO and endO methods for each banded _vector simply call the underlying methods of the original vector. For the unpacked case, the begin 0 and end 0 methods have to offset according to the bandwidth. The bulk of MTL code for the banded adapter was constructed at the TYoD level, without respect to row and column orientation. This allows the single banded class to be used with both row and column oriented matrices. Figure 11 gives some of the implementation of the banded_vector class.

Begin-rows 0 ; a. subJnatrix(i,j,m,n) X Inote row or column? banded, etc. ncolsO == 0 copy assignment create an m x n matrix element access row dimension column dimension create sub matrix Table 9. Orientation adapter requirements. A Framework for Numerical Linear Algebra typedef typedef typedef typedef 33 typename TwoD::minor_iterator column_2Diterator; typename TwoD::MajorVector RowVector; typename TwoD::MinorVector ColumnVector; column transpose_type; row(int nrows, int ncols) : TwoD(nrows, ncols) { } const_reference operator()(int row, int col) const { return TwoD::operator()(row,col); } row_2Diterator begin_rows() { return begin_major(); } row_2Diterator end_rows() { return end_major(); } column_2Diterator begin_columns() { return begin_minor(); } column_2Diterator end_columns() { return end_minor(); } RowVectorRef row_vector(int i) { return major_vector(i); } ColumnVectorRef column_vector(int j) { return minor_vector(j); } }; There are often situations when one wishes to operate on the transpose of a matrix for one particular operation.

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