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This thesis summarizes the work of the author on visualization of performance data in parallel Computational Fluid Dynamics (CFD) simulations. Current performance analysis tools are unable to show their data on top of complex simulation geometries (e.g. an aircraft engine). But in CFD simulations, performance is expected to be affected by the computations being carried out, which in turn are tightly related to the underlying computational grid. Therefore it is imperative that performance data is visualized on top of the same computational geometry which they originate from. However, performance tools have no native knowledge of the underlying mesh of the simulation. This scientific gap can be filled by merging the branches of HPC performance analysis and in situ visualization of CFD simulations data, which shall be done by integrating existing, well established state-of-the-art tools from each field. In this threshold, an extension for the open-source performance tool Score-P was designed and developed, which intercepts an arbitrary number of manually selected code regions (mostly functions) and send their respective measurements – amount of executions and cumulative time spent – to the visualization software ParaView – through its in situ library, Catalyst –, as if they were any other flow-related variable. Subsequently the tool was extended with the capacity to also show communication data (messages sent between MPI ranks) on top of the CFD mesh. Testing and evaluation are done with two industry-grade codes: Rolls-Royce’s CFD code, Hydra, and Onera, DLR and Airbus’ CFD code, CODA. On the other hand, it has been also noticed that the current performance tools have limited capacity of displaying their data on top of three-dimensional, framed (i.e. time-stepped) representations of the cluster’s topology. Parallel to that, in order for the approach not to be limited to codes which already have the in situ adapter, it was extended to take the performance data and display it – also in codes without in situ – on a three-dimensional, framed representation of the hardware resources being used by the simulation. Testing is done with the Multi-Grid and Block Tri-diagonal NAS Parallel Benchmarks (NPB), as well as with Hydra and CODA again. The benchmarks are used to explain how the new visualizations work, while real performance analyses are done with the industry-grade CFD codes. The proposed solution is able to provide concrete performance insights, which would not have been reached with the current performance tools and which motivated beneficial changes in the respective source code in real life. Finally, its overhead is discussed and proven to be suitable for usage with CFD codes. The dissertation provides a valuable addition to the state of the art of highly parallel CFD performance analysis and serves as basis for further suggested research directions.

Three-dimensional volume data is routinely produced, at increasingly high spatial resolution, in computer simulations and image acquisition tasks. In-situ visualization, the visualization of an experiment or simulation while it is running, enables new modes of interaction, including simulation steering and experiment control. These can provide the scientist a deeper understanding of the underlying phenomena, but require interactive visualization with smooth viewpoint changes and zooming to convey depth perception and spatial understanding. As the size of the volume data increases, however, it is increasingly challenging to achieve interactive visualization with smooth viewpoint changes. This thesis presents an end-to-end solution for interactive in-situ visualization based on novel extensions proposed to the Volumetric Depth Image (VDI) representation. VDIs are view-dependent, compact representations of volume data than can be rendered faster than the original data. Novel methods are proposed in this thesis for generating VDIs on large data and for rendering them faster. Together, they enable interactive in situ visualization with smooth viewpoint changes and zooming for large volume data. The generation of VDIs involves decomposing the volume rendering integral along rays into segments that store composited color and opacity, forming a representation much smaller than the volume data. This thesis introduces a technique to automatically determine the sensitivity parameter that governs the decomposition of rays, eliminating the need for manual parameter tuning in the generation of a VDI. Further, a method is proposed for sort-last parallel generation and compositing of VDIs on distributed computers, enabling their in situ generation with distributed numerical simulations. A low latency architecture is proposed for the sharing of data and hardware resources with a running simulation. The resulting VDI can be streamed for interactive visualization. A novel raycasting method is proposed for rendering VDIs. Properties of perspective projection are exploited to simplify the intersection of rays with the view-dependent segments contained within the VDI. Spatial smoothness in volume data is leveraged to minimize memory accesses. Benchmarks are performed showing that the method significantly outperforms existing methods for rendering the VDI, and achieves responsive frame rates for High Definition (HD) display resolutions near the viewpoint of generation. Further, a method is proposed to subsample the VDI for preview rendering, maintaining high frame rates even for large viewpoint deviations. The quality and performance of the approach are analyzed on multiple datasets, and the contributions are provided as extensions of established open-source tools. The thesis concludes with a discussion on the strengths, limitations, and future directions for the proposed approach.