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 recent com­ puters, it is crucial to swiftly increase the functionality and reliability of the software program to boot, and infrequently with no need an appropriate mathematical thought on hand. within the dealing with of a growing number of complicated real-life numerical difficulties in all types of functions, a latest object-oriented de­ signal and implementation of software program instruments has turn into a vital part. The significant demanding situations posed through the call for for effective object-oriented software program in all components of clinical computing make it essential to trade rules and stories from as many alternative resources as attainable. prompted by way of the luck of the 1st assembly of this sort in Norway in 1996, we determined to arrange one other overseas Workshop on sleek software program instruments for medical Computing, also known as SciTools'98. This workshop happened in Oslo, Norway, September 14-16, 1998. The ob­ jective used to be back to supply an open discussion board for trade and dialogue of recent, cutting-edge software program strategies utilized to hard numerical difficulties. The association used to be undertaken together by means of the study institute SINTEF utilized arithmetic, the Departments of arithmetic and Infor­ matics on the college of Oslo, and the corporate Numerical items AS.

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The job of a matrix orientation adapter is to map the major and minor aspects of a TwoD container to the corresponding row or column of a matrix. There are two orientation adapters, the row and column classes. The mapping they perform involves both member functions and typedefs. lllaj or 0 function. rowO method, while the column adapter maps this to the begin_columnO method. A TwoD container also has internal typedefs such as MinorVector. The row adapter maps this type to ColumnVector while the column adapter maps this to RowVector.

It is implemented in terms of a FAST algorithm, in this case transformO. The implementation of the BLAIS addO is listed below. The addO function is implemented with a class and its constructor in order to provide a simple syntax for its use. template struct add { template inline add(Iter1 x, Iter2 y) { typedef typename iterator_traits::value_type T; fast::transform(x, cnt(), y, y, plus(»; } }; The example below shows how the add 0 routine can be used.

Many linear algebra packages provide this capability through an extra parameter in the interface that causes a dispatch to a specialized version of the operation. The only difference in the specialized versions is the mapping of the row and column index of an element to where it is stored in memory. As discussed in the beginning of this section, the mapping of indices in an MTL matrix is controlled by the orientation adapter, not hard coded into the subroutine. Therefore, by merely switching the type of orientation adapter associated with the matrix, one can make the normal algorithm operate on the transpose of the matrix.

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