Invited Talk: Symbiotic Modeling and High-Performance Simulation

Symbiotic Modeling and High-Performance Simulation

January 19, 2017

Department of Computer Science, Colorado School of Mines
Host: Professor Tracy Camp

Abstract: Modeling and simulation plays an important role in the design analysis and performance evaluation of complex systems. Many of these systems, such as the internet and high-performance computing systems, involve a huge number of interrelated components and processes. Complex behaviors emerge as these components and processes inter-operate across multiple scales at various granularities. Modeling and simulation must be able to provide sufficiently accurate results while coping with the scale and the complexity of these systems. My talk will focus on some of our latest advances in high-performance modeling and simulation techniques. I will focus on two specific case studies, one on network emulation and the other on high-performance computing (HPC) modeling.
In the first case, I will present a novel distributed network emulation mechanism based on modeling symbiosis. Mininet is a container-based emulation environment that can study networks consisted of virtual hosts and OpenFlow-enabled virtual switches on Linux. It is well-known, however, that experiments using Mininet may lose fidelity for large-scale networks and heavy traffic load. We propose a symbiotic approach, where an abstract network model is used to coordinate the distributed emulation instances superimposed to represent the target network. In doing so, we can effectively study the behavior of real implementation of network applications on large-scale networks in a distributed environment.
In the second case, I will present our latest work on performance modeling of HPC architectures and applications. In collaboration with the Los Alamos National Laboratory, we have developed a highly efficient simulator, called Performance Prediction Toolkit (PPT), which can facilitate rapid and accurate performance prediction of large-scale scientific applications on existing and future HPC architectures.