The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: ISAV 2022: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization
Authors: Zhe Wang (Rutgers University), Matthieu Dorier (Argonne National Laboratory (ANL)), and Manish Parashar (University of Utah)
Abstract: In situ approaches enable performing data analysis/visualization (ana/vis) close to the data source and running them on the same system. However, variations in the simulation data and the diversity of underlying HPC environments increase the difficulty of adjusting the in situ processing configurations adaptively. Triggers are an emerging strategy that follows the autonomic computing paradigm to optimize when and how to execute in situ ana/vis tasks. By inspecting indicators, the trigger can flexibly issue customized control instructions to optimize the execution of in situ ana/vis tasks in real-time. This position paper formalizes the elements of the trigger mechanism according to the definition of autonomic computing. It uses the formalization as a guideline to summarize the research status of different aspects of the trigger mechanism for in situ processing, including (1) where to execute ana/vis tasks, (2) resource allocation of ana/vis tasks, and (3) when to execute ana/vis tasks.