TY - GEN
T1 - Genetic epidemiology, parallel algorithms, and workstation networks
AU - Chamberlain, R. D.
AU - Peterson, G. D.
AU - Franklin, M. A.
AU - Province, M. A.
N1 - Funding Information:
'This material is based upon work supported by the National Science Foundation under grants MIP-9309658a nd CCR- 9021041 and the National Institutes of Health under grant GM28719.
Funding Information:
This material is based upon work supported by the National Science Foundation under grants MIP-9309658 and CCR-9021041 and the National Institutes of Health under grant GM28719.
Publisher Copyright:
© 1995 IEEE.
PY - 1995
Y1 - 1995
N2 - Many interesting problems in genetic epidemiology are formulated as non-linear optimization problems using the Gemini/Almini 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 with 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 parallelism and discuss two preliminary implementations that demonstrate the potential benefits of cost-effective 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.
AB - Many interesting problems in genetic epidemiology are formulated as non-linear optimization problems using the Gemini/Almini 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 with 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 parallelism and discuss two preliminary implementations that demonstrate the potential benefits of cost-effective 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.
UR - http://www.scopus.com/inward/record.url?scp=33847200672&partnerID=8YFLogxK
U2 - 10.1109/HICSS.1995.375346
DO - 10.1109/HICSS.1995.375346
M3 - Conference contribution
AN - SCOPUS:33847200672
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 101
EP - 111
BT - Proceedings of the 28th Annual Hawaii International Conference on System Sciences, HICSS 1995
PB - IEEE Computer Society
T2 - 28th Annual Hawaii International Conference on System Sciences, HICSS 1995
Y2 - 3 January 1995 through 6 January 1995
ER -