Automatic selection of sequence transformations

Automatic Parameter Selection for Sequence Similarity Search

We show that simulated annealing search can be used to automatically select parameters and find highly similar data regions using a modified version of the DNA-DNA Sequence Similarity Search program. We call this modified program AutoSimS. We use the average score of high-scoring chains to measure the goodness of the resulting sequence similarity search, and use adaptive simulated annealing to ...

Automatic Verification of Algebraic Transformations

Programmers applying nontrivial code transformations are often faced with the problem of ensuring the functional equivalence of original and transformed programs. A pragmatic approach to the problem is to provide a tool to the programmers to check the equivalence of the two programs after applying the transformations. In prior work we have developed such a tool to handle important transformatio...

Automatic selection of high-order transformations in the IBM XL FORTRAN compilers

The IBM ASTl optimizer provides the foundation for high-order transformations and automatic shared-memory parallelization in the latest IBM XL FORTRAN (XLF) compilers for RS/6000'" and PowerPC@ uniprocessors and symmetric multiprocessors (SMPs), and for automatic distributed-memory parallelization in the IBM XL High-Performance FORTRAN (XLHPF) compiler for the SP' " distributed-memory multiproc...

Scalar Levin-type Sequence Transformations

Sequence transformations are important tools for the convergence acceleration of slowly convergent scalar sequences or series and for the summation of divergent series. The basic idea is to construct from a given sequence { sn} a new sequence { s ′ n} = T ({ sn} ) where each s ′ n depends on a finite number of elements sn1 , . . . , snm . Often, the sn are the partial sums of an infinite series...

Sil Transformations on Sequence Edges