Rebecca J. Parsons

A case study in experimental design applied to genetic algorithms with applications to DNA sequence assembly

Synoptic AbstractExperimental design and response surface methodology is applied to tuning the parameters of an optimization program employing genetic algorithms. Attention is directed to the combinatorially challenging DNA sequence assembly problem. Fine tuning of a 10K size test problem leads to a considerably improved solution to a 35K problem of sequence assembly that is of significant biological interest.

The Heterogeneous Bulk Synchronous Parallel Model

Trends in parallel computing indicate that heterogeneous parallel computing will be one of the most widespread platforms for computation-intensive applications. A heterogeneous computing environment offers considerably more computational power at a lower cost than a parallel computer. We propose the Heterogeneous Bulk Synchronous Parallel (HBSP) model, which is based on the BSP model of parallel computation, as a framework for developing applications for heterogeneous parallel environments. HBSP enhances the applicability of the BSP model by incorporating parameters that reflect the relative speeds of the heterogeneous computing components. Moreover, we demonstrate the utility of the model by developing parallel algorithms for heterogeneous systems.

Exploiting hierarchy in heterogeneous environments

Heterogeneous cluster environments are becoming an increasingly popular platform for executing parallel applications. Efficient heterogeneous parallel applications must account for the differences inherent in such an environment. Specifically, faster machines should possess more data items than their slower counterparts and communication should be minimized over slow network links. We propose the -Heterogeneous Bulk Synchronous Parallel (HBSP ) model, which is based on the BSP model of computation, as a framework for developing applications for heterogeneous systems. The BSP model is appropriate for -level (one communication network) heterogeneous systems. HBSP extends BSP hierarchically to address level heterogeneous machines. The utility of the model is demonstrated through the design and analysis of the gather and one-to-all broadcast operations. Experimental results demonstrate the improved performance that results from effectively exploiting the heterogeneity of the underlying system. By hiding the non-uniformity of the underlying system from the application developer, the HBSP model offers a framework that encourages the design of heterogeneous parallel software.

The design and applications of a recursive molecular modeling framework

In this paper, we present a recursive molecular model that is suitable for multi-resolution analysis in a variety of application areas. Our approach allows ease of use by computer scientists and biologists by proposing a software interface for molecular analysis that hides programming details. We demonstrate that our design is flexible enough for use in desktop analytical applications, in large-scale parallel simulations, and as a server for remote molecular analysis across wide-area networks.

Evolution of cooperating and competing individuals in a dynamic fitness environment

Evolving a single individual does not provide a solution when a set of individuals is needed to address different aspects of the problem. Genetic algorithms, however, are typically used to evolve a single individual. We have generalized previous work on modeling the immune system and developed a fitness method that allows a single run of a genetic algorithm to evolve a suite of individuals that compete with each other for fitness and yet cooperate to solve a problem. The method is a form of tournament fitness where individuals compete for fitness with other members of the population. The competitions vary throughout the run, resulting in a changing fitness environment. Experimental results and a preliminary model are described that verify the validity of the approach. We also present explanations for unexpected results from our previous work.

Recursive, object-oriented structures for molecular modeling

In this paper, we present a molecular modeling approach based on recursive object-oriented class instances. Our approach allows ease of use by the scientist and includes a heuristic for evaluating molecular interaction and rendering at multiple levels of detail. Our implementation in C++ employs abstractions to encapsulate the implementation and details of the computations. Visualization is accomplished with OpenGL or the Visualization Toolkit (VTK), an application-independent scientific visualization library.

When an advantage is not an advantage

Discussion of the merits and shortcomings of affirmative action (AA) has raged at all levels and in many forums and has been the concern of many policymakers, including President Clinton. Notably absent from the discussion is the perception of AA, and the effect of the angry backlash on women and minorities. Recently, the question of whether women enjoy an “unfair advantage” was posted electronically on Systers, a private organization of over 1,800 professional women in the male-dominated field of computing. The 42 responses contained strong personal stories from women at every level of professional growth who had all dealt with the issues of gender bias and AA at each step of the way.