Alternatives for parallel Krylov subspace basis computation

Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algebra. Vectors in these subspaces are manipulated via their representation onto orthonormal bases. Nowadays, on serial computers, the method of Arnoldi is considered as a reliable technique for constructing such bases. However, although easily parallelizable, this technique is not as scalable as expected for communications. In this work we examine alternative methods aimed at overcoming this drawback. Since they retrieve upon completion the same information as Arnoldi's algorithm does, they enable us to design a wide family of stable and scalable Krylov approximation methods for various parallel environments. We present timing results obtained from their implementation on two distributed-memory multiprocessor supercomputers: the Intel Paragon and the IBM Scalable POWERparallel SP2. (C) 1997 by John Wiley & Sons, Ltd.

Optical encoding of microbeads for gene screening: alternatives to microarrays

Rapid access to genetic information is central to the revolution presently occurring in the pharmaceutical industry, particularly In relation to novel drug target identification and drug development. Genetic variation, gene expression, gene function and gene structure are just some of the important research areas requiring efficient methods of DNA screening. Here, we highlight state-of-the-art techniques and devices for gene screening that promise cheaper and higher-throughput yields than currently achieved with DNA microarrays. We include an overview of existing and proposed bead-based strategies designed to dramatically increase the number of probes that can be interrogated in one assay. We focus, in particular, on the issue of encoding and/or decoding (bar-coding) large bead-based libraries for HTS.