Parallel computing in biomedical research and the search for peta-scale biomedical applications

The recent revolution in biomedical research opens new possibilities for applications of parallel computing that did not previously exist. This paper discusses three parallel applications useful in medicine and bioinformatics-PENELOPE. GeneIndex. and fastDNAml-in terms of their scaling characteristics and the way they are used by biomedical researchers. PENE-LOPE is a code that may be used to enhance radiation therapy for brain cancers. GeneIndex is a tool for interacting with genome sequence data when studying its underlying structure. fastDNAml is a tool for inferring evolutionary relationships from DNA sequence data. None are peta-scale applications, but all are useful applications of parallel computing technology in biomedical research. Biologists may not be familiar with the promise that parallel computing has for enhancing biomedical research. The parallel computing community will have its greatest impact on biomedical research only if significant effort is expended in reaching out to the biomedical research community. As the search for peta-scale applications in biomedical research continues, standard techniques in parallel computing may result in useful-and even potentially lifesaving-applications at more modest scales of parallelism. The ability of parallel computing techniques to enable more interactive analyses of biomedical data is particularly important.