This will be a half-day tutorial on Parallel Computing-related issues in Bioinformatics and Computational Biology (BCB). The target audience will be scientifically-literate computational researchers who are not currently engaged in BCB. About half of the tutorial will be an overview of a representative collection of basic life science and medical research problems contemporary to this rapidly expanding field. The second half of the tutorial will focus attention on some of the problems in BCB that are most in need of high-performance computing and networking. The tutorial will provide a basic level of introduction to these problems, and is intended to serve to introduce this area of inter-disciplinary research to people interested in becoming partially involved in applying their backgrounds in Parallel Computing to BCB.

The concept of fine-grained parallelism is considered in the context of its application in simulation of spatially distributed processes. It comprises models, algorithms and computing technologies exhibiting two following properties: 1) spatial parallelism (at any discrete time the next values of the spatial function in all points of the space are allowed to be computed in parallel), and 2) locality (the computation for any point uses as variables the values of the function in its fixed vicinity). The scope of fine-grain spatial dynamics models is classified and illustrated by examples, the domain of application of each class being specified. Theoretical background of fine-grained parallel computations is given in brief. Computational properties (accuracy, stability, coarse-grained parallelization efficiency) are discussed, and methods of fine-grained algorithms synthesis are presented and shown at work by examples.