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A novel approach is presented for recording high volume data about ray tracing rendering systems' runtime state and its subsequent dynamic analysis and interactive visualization in the algorithm computational domain. Our framework extracts light paths traced by the system and leverages on a powerful filtering subsystem, helping interactive visualization and exploration of the desired subset of recorded data. We introduce a versatile data logging format and acceleration structures for easy access and filtering. We have implemented a plugin based framework and a tool set that realize all ideas presented in this paper. The framework provides data logging API for instrumenting production-ready, multithreaded, distributed renderers. The framework visualization tool enables deeper understanding of the ray tracing algorithms for novices, as well as for experts.

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Debugging is a very time consuming task which is not well supported by existing tools. The existing methods do not provide tools enabling optimal developers’ productivity when debugging regressions in complex systems. In this paper we describe a possible solution aiding differential debugging. The differential debugging technique performs analysis of the regressed system and identifying the cause of the unexpected behavior by comparing to a previous version of the same system. The prototype, idd, inspects two versions of the executable – a baseline and a regressed version. The interactive debugging session runs side by side both executables and allows to examine and to compare various internal states. The architecture can work with multiple information sources comparing data from different tools. We also show how idd can detect performance regressions using information from third-party performance facilities. We illustrate how in practice we can quickly discover regressions in large systems such as the clang compiler.