Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations

Abstract

Fig. 1. Network traffic resulting from two different runs of the parallel simulation pF3D. This simulation models laser plasma interaction inside of a hohlraum chamber by decomposing the domain into a set of blocks (left). Depending on how data blocks are mapped to processor cores (middle), different communication patterns occur. When staggering data placement (bottom right) we observe significantly more balanced communication compared to a default mapping similar to how the domain is decomposed (top right).Abstract-The performance of massively parallel applications is often heavily impacted by the cost of communication among compute nodes. However, determining how to best use the network is a formidable task, made challenging by the ever increasing size and complexity of modern supercomputers. This paper applies visualization techniques to aid parallel application developers in understanding the network activity by enabling a detailed exploration of the flow of packets through the hardware interconnect. In order to visualize this large and complex data, we employ two linked views of the hardware network. The first is a 2D view, that represents the network structure as one of several simplified planar projections. This view is designed to allow a user to easily identify trends and patterns in the network traffic. The second is a 3D view that augments the 2D view by preserving the physical network topology and providing a context that is familiar to the application developers. Using the massively parallel multi-physics code pF3D as a case study, we demonstrate that our tool provides valuable insight that we use to explain and optimize pF3D's performance on an IBM Blue Gene/P system.

Characterization and modeling of PIDX parallel I/O for performance optimization

“…We use a projection of the 3D network topology provided by Boxfish [21], an integrated performance analysis and visualization tool developed at Lawrence Livermore National Laboratory. Each image of Figure 3 shows all the network links along two torus dimensions aggregated into bundles along the third dimension.…”

Combing the Communication Hairball: Visualizing Parallel Execution Traces using Logical Time

“…Different mappings of the 3D logical process grid of pF3D onto the 5D torus of BG/Q can make a significant difference in how messages are routed on the network and in turn, performance [6]. The effect was previously studied on a 3D torus interconnect with the aid of a visualization specific to that interconnect topology [26]. As such visualizations are not available for all interconnects, including the BG/Q's 5D torus, we explore performance under different process mappings using tracing and trace visualization.…”

CommGram: A New Visual Analytics Tool for Large Communication Trace Data

“…Sigovan et al [16] also presented a visual network analysis method for the trace data from large parallel I/O systems. Landge et al [17] introduced a method that combines the 2D and 3D views to visualize the network traffic of large-scale simulations on a supercomputer.…”