A Case Study on Providing Accessibility-Focused In-Transit Architectures for Neural Network Simulation and Analysis

Due to the ever-increasing availability of high-performance computing infrastructure, developers can simulate increasingly complex models. However, the increased complexity comes with new challenges regarding data processing and visualization due to the sheer size of simulations. Exploring simulation results needs to be handled efficiently via in-situ/in-transit analysis during run-time. However, most existing in-transit solutions require sophisticated and prior knowledge and significant alteration to existing simulation and visualization code, which produces a high entry barrier for many projects. In this work, we report how Insite, a lightweight in-transit pipeline, provided in-transit visualization and computation capability to various research applications in the neuronal network simulation domain. We describe the development process, including feedback from developers and domain experts, and discuss implications.