Genetic epidemiology, parallel algorithms, and workstation networks
نویسندگان
چکیده
Many interesting problems in genetic epidemiology are formulated as non-linear optimization problems wing the Gemini/AImini library of routines. Because of the wide availability of networked workstations, we investigate cost-effectively improving the performance of the Gemini/Almini library by exploiting parallelism m’th a set of workstations connected via a local-area network. Instrumentation of the Gemini/Almini optimization routines reveals significant potential for improving performance via parallelism. Using these instrumentation results, we identify promising targets of pamllelism and discuss two preliminary implementations that demonstrate the potential benefits of costeffective parallel implementations. By applying parallelism to the Almini/Gemini routines, we hope to potentially improve the performance of a large number of genetic epidemiological applications.
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تاریخ انتشار 1995