Simulation-based Performance Analysis and Tuning for a Two-level Directly Connected System
International Conference on Parallel and Distributed Systems (ICPADS) 2011
Publication Type: Paper
Repository URL: papers/201107_BigSimBW
Abstract
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.
TextRef
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
People
- Ehsan Totoni
- Abhinav Bhatele
- Eric Bohm
- Nikhil Jain
- Celso Mendes
- Ryan Mokos
- Gengbin Zheng
- Laxmikant Kale
Research Areas