Authors:
Tae-Hyuk Ahn
1
;
Damian Dechev
2
;
Heshan Lin
1
;
Helgi Adalsteinsson
3
and
Curtis Janssen
3
Affiliations:
1
Virginia Tech, United States
;
2
University of Central Florida and Sandia National Laboratories, United States
;
3
Sandia National Laboratories, United States
Keyword(s):
Exascale architecture simulator, mpiBLAST, Performance and scalability modeling.
Related
Ontology
Subjects/Areas/Topics:
Complex Systems Modeling and Simulation
;
Discrete-Event Simulation
;
Formal Methods
;
Model-Driven Simulation Engineering
;
Multiscale Simulation
;
Optimization Issues
;
Simulation and Modeling
Abstract:
The next decade will see a rapid evolution of HPC node architectures as power and cooling constraints are limiting increases in microprocessor clock speeds and constraining data movement. Future and current HPC applications will have to change and adapt as node architectures evolve. The application of advanced cycle accurate node architecture simulators will play a crucial role for the design and optimization of future data intensive applications. In this paper, we present our simulation-based framework for analyzing the scalability and performance of a number of critical optimizations of a massively parallel genomic search application, mpiBLAST, using an advanced macroscale simulator (SST/macro). In this paper we report the use of our framework for the evaluation of three potential improvements of mpiBLAST: enabling high-performance parallel output, an approach for caching database fragments in memory, and a methodology for pre-distributing database segments. In our experimental set
up, we performed query sequence matching on the genome of the yellow fever mosquito, Aedes aegypti.
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