Low-Overhead LogGP Parameter Assessment for Modern Interconnection Networks

Network performance measurement and prediction is very important to predict the running time of high performance computing applications. The LogP model family has been proven to be a viable tool to assess the communication performance of parallel architectures. However, non-intrusive LogP parameter assessment is still a very difficult task. We compare well known measurement methods for Log(G)P parameters and discuss their accuracy and network contention. Based on this, a new theoretically exact measurement method that does not saturate the network is derived and explained in detail. Our method only uses benchmarked values instead of computed parameters to compute other parameters to avoid propagation of first-order errors. A methodology to detect protocol changes in the underlying communication subsystem is also proposed. The applicability of our method and the protocol change detection is shown for the low-level API as well as MPI implementations of different modern high performance interconnection networks. The whole method is implemented in the tool Netgauge and it is available as open source to the public.