LOOM: Interweaving tightly coupled visualization and numeric simulation framework

Abstract

Traditional post-hoc high-fidelity scientific visualization (HSV) of numerical simulations requires multiple I/O check-pointing to inspect the simulation progress. The costs of these I/O operations are high and can grow exponentially with increasing problem sizes. In situ HSV dispenses with costly check-pointing I/O operations, but requires additional computing resources to generate the visualization, increasing power and energy consumption. In this paper we present LOOM, a new interweaving approach supported by a task scheduling framework to allow tightly coupled in situ visualization without significantly adding to the overall simulation runtime. The approach exploits the idle times of the numerical simulation threads, due to workload imbalances, to perform the visualization steps. Overall execution time (simulation plus visualization) is minimized. Power requirements are also minimized by sharing the same computational resources among numerical simulation and visualization tasks. We demonstrate that LOOM reduces time to visualization by 3× compared to a traditional noninterwoven pipeline. Our results here demonstrate good potential for additional gains for large distributed-memory use cases with larger interleaving opportunities. CCS CONCEPTS• Computing methodologies → Parallel algorithms.

A Hybrid in Situ Approach for Cost Efficient Image Database Generation

“…Dirand's TINS system [32] approached the problem from a task-based perspective, with resources being allocated for analytics when such tasks emerged. LOOM [33] is a framework for tightly coupled in situ visualization that interweaves tasks to reduce idle times of simulation threads. While our approach is also elastic, it differs from these previous works in our focus: achieving cost savings by dynamically arranging execution to minimize fundamental in situ inefficiencies.…”