Simulation-based Performance Analysis and Tuning for a Two-level Directly Connected System

Hardware and software co-design is becoming increasingly important due to complexities in supercomputing architectures. Simulating applications before there is access to the real hardware can assist machine architects in making better design decisions that can optimize application performance. At the same time, the application and runtime can be optimized and tuned beforehand. BigSim is a simulation-based performance prediction framework designed for these purposes. It can be used to perform packet-level network simulations of parallel applications using existing parallel machines. In this paper, we demonstrate the utility of BigSim in analyzing and optimizing parallel application performance for future systems based on the PERCS network. We present simulation studies using benchmarks and real applications expected to run on future supercomputers. Future petascale systems will have more than 100,000 cores, and we present simulations at that scale.

Ehsan Totoni, Abhinav Bhatele, Eric Bohm, Nikhil Jain, Celso Mendes, Ryan Mokos, Gengbin Zheng, Laxmikant Kale,, Simulation-based Performance Analysis and Tuning for a Two-level Directly Connected System, Proceedings of the 17th IEEE International Conference on Parallel and Distributed Systems, 2011

@inproceedings{BWICPADS2011,
  author = {Ehsan Totoni and Abhinav Bhatele and Eric Bohm and Nikhil Jain and Celso Mendes and Ryan Mokos and Gengbin Zheng and Laxmikant Kale},
  title = {Simulation-based Performance Analysis and Tuning for a Two-level Directly Connected System},
  booktitle = {Proceedings of the 17th IEEE International Conference on Parallel and Distributed Systems},
  year = {2011},
  month = {December},
}