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

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

To make complete use of the ever expanding features of recent com­ puters, it is crucial to quickly increase 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 a growing number of advanced real-life numerical difficulties in all kinds of functions, a latest object-oriented de­ signal and implementation of software program instruments has turn into a vital part. The huge demanding situations posed by means of the call for for effective object-oriented software program in all parts of clinical computing make it essential to trade principles and studies from as many alternative assets as attainable. influenced by way of the luck of the 1st assembly of this sort in Norway in 1996, we determined to prepare one other foreign Workshop on glossy software program instruments for medical Computing, sometimes called SciTools'98. This workshop came about 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 contemporary, cutting-edge software program ideas utilized to hard 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 collage of Oslo, and the corporate Numerical gadgets AS.

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Loop blocking for cache is used to attain high levels of performance here. Finally, for matrix sizes larger than approximately N = 1024, performance can be affected by conflict misses in the cache. The results for ATLAS and Fortran BLAS fall precipitously at this point. To attain good performance in the face of conflict misses (in low associativity caches) blockcopy techniques as described in [18) are used. Note that performance effects are cumulative. For instance, the Netlib BLAS do not use any of the techniques listed above for performance enhancement.

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. The trans () helper function is provided so that it is convenient to the user to switch the orientation of a matrix. The implementation of trans 0 and an example of its use are presented below.

J. Siek, A. Lumsdaine 30 template class scale_iterator { public: scale_iterator(const Iterator& x, const value_type& a) : current (x) , alpha (a) { } value_type operator*() const { return alpha * *current; } scale_iterator& operator++ () { ++current; return *this; } II ... protected: Iter current; value_type alpha; }; At first glance one may think that the scale-iterator introduces overhead which would have significant performance implications for inner loops. In fact modern compilers will inline the operator* 0, and propagate the scalar's value to where it is used if it is a constant (known at compile time).

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