Response-Time Analysis of Bundled Gang Tasks Under Partitioned FP Scheduling

Abstract

The study of parallel task models for real-time systems has become fundamental due to the increasing computational demand of modern applications. Recently, gang scheduling has gained attention for improving performance in tightly synchronized parallel applications. Nevertheless, existing studies often overestimate computational demand by assuming a constant number of cores for each task. In contrast, the bundled model accurately represents internal parallelism by means of a string of segments demanding for a variable number of cores. This model is particularly relevant to modern real-time systems, as it allows transforming general parallel tasks into bundled tasks while preserving accurate parallelism. However, it has only been analyzed for global scheduling, which carries analytical pessimism and considerable run-time overheads. This paper introduces two response-time analysis techniques for parallel real-time tasks under partitioned, fixed-priority gang scheduling under the bundled model, together with a set of specialized allocation heuristics. Experimental results compare the proposed methods against state-of-the-art approaches.