University of North Carolina at Chapel Hill Graduate School
Doi
Abstract
Developments in the semiconductor industry in the previous decades have made possible computing platforms with very large computing capacities that, in turn, have stimulated the rapid progress of computationally intensive computer vision (CV) algorithms with highly parallelizable structure (often represented as graphs). Applications using such algorithms are the foundation for the transformation of semi-autonomous systems (e.g., advanced driver-assist systems) to future fully-autonomous systems (e.g., self-driving cars). Enabling mass-produced safety-critical systems with full autonomy requires real-time execution guarantees as a part of system certification.Since multiple CV applications may need to share the same hardware platform due to size, weight, power, and cost constraints, system component isolation is necessary to avoid explosive interference growth that breaks all execution guarantees. Existing software certification processes achieve component isolation through time partitioning, which can be broken by accelerator usage, which is essential for high-efficacy CV algorithms.The goal of this dissertation is to make a first step towards providing real-time guarantees for safety-critical systems by analyzing the scheduling of highly parallel accelerator-using workloads isolated in system components. The specific contributions are threefold.First, a general method for graph-based workloads’ response-time-bound reduction through graph structure modifications is introduced, leading to significant response-time-bound reductions. Second, a generalized real-time task model is introduced that enables real-time response-time bounds for a wider range of graph-based workloads. A proposed response-time analysis for the introduced model accounts for potential accelerator usage within tasks. Third, a scheduling approach for graph-based workloads in a single system component is proposed that ensures the temporal isolation of system components. A response-time analysis for workloads with accelerator usage is presented alongside a non-mandatory schedulability-improvement step. This approach can help to enable component-wise certification in the considered systems.Doctor of Philosoph
