TY - GEN
T1 - Sensitivity analysis of biomolecular simulations using symbolic models
AU - Alam, Sadaf R.
AU - Bhatia, Nikhil
AU - Vetter, Jeffrey S.
PY - 2007
Y1 - 2007
N2 - Performance and scaling of biomolecular simulations frameworks largely depends on not only the workload characteristics of the simulations but also the design of underlying processor architecture and interconnection networks. Because construction of Teraflops and Petaflops scale prototype systems for evaluation alone is impractical and cost-prohibitive, architects use analytical models of workloads and architecture simulators to guide their design decisions and tradeoffs. To address the problem of providing scalable yet precise input for network simulators, we have developed a technique to model symbolically the communication patterns of production-level scientific applications to study workload growth rates and to carry out sensitivity analysis. We apply our symbolic modeling scheme to the Particle Mesh Ewald (PME) implementation in the sander package of the AMBER framework and demonstrate how the increase in computation, memory and communication requirements impact the performance and scaling of the PME method on the next-generation massively-parallel systems.
AB - Performance and scaling of biomolecular simulations frameworks largely depends on not only the workload characteristics of the simulations but also the design of underlying processor architecture and interconnection networks. Because construction of Teraflops and Petaflops scale prototype systems for evaluation alone is impractical and cost-prohibitive, architects use analytical models of workloads and architecture simulators to guide their design decisions and tradeoffs. To address the problem of providing scalable yet precise input for network simulators, we have developed a technique to model symbolically the communication patterns of production-level scientific applications to study workload growth rates and to carry out sensitivity analysis. We apply our symbolic modeling scheme to the Particle Mesh Ewald (PME) implementation in the sander package of the AMBER framework and demonstrate how the increase in computation, memory and communication requirements impact the performance and scaling of the PME method on the next-generation massively-parallel systems.
KW - Biomolecular simulations
KW - High performance computing
KW - Performance analysis
KW - Performance modeling and prediction
KW - Scalability
UR - http://www.scopus.com/inward/record.url?scp=47649127140&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2007.4375579
DO - 10.1109/BIBE.2007.4375579
M3 - Conference contribution
AN - SCOPUS:47649127140
SN - 1424415098
SN - 9781424415090
T3 - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
SP - 294
EP - 300
BT - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
T2 - 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Y2 - 14 January 2007 through 17 January 2007
ER -