We consider the scheduling of a sporadic real-time task system on an identical multiprocessor. Though Pfair algorithms are theoretically optimal for such task systems, in practice, their runtime overheads can significantly reduce the amount of useful work that is accomplished. On the other hand, if all deadlines need to be met, then every known non-Pfair algorithm requires restrictions on total system utilization that can approach approximately 50% of the available processing capacity. This may be overkill for soft real-time systems, which can tolerate occasional or bounded deadline misses (i.e. bounded tardiness). In this paper we derive tardiness bounds under preemptive and non-preemptive global EDF when the total system utilization is not restricted, except that it not exceed the available processing capacity. Hence, processor utilization can be improved for soft real-time systems on multiprocessors. Our tardiness bounds depend on the total system utilization and per-task utilizations and execution costs-the lower these values, the lower the tardiness bounds. As a final remark, we note that global EDF may be superior to partitioned EDF for multiprocessorbased soft real-time systems in that the latter does not offer any scope to improve system utilization even if bounded tardiness can be tolerated.

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Multicore architectures, which have multiple processing units on a single chip, are widely viewed as a way to achieve higher processor performance, given that thermal and power problems impose limits on the performance of single-core designs. Accordingly, several chip manufacturers have already released, or will soon release, chips with dual cores, and it is predicted that chips with up to 32 cores will be available within a decade. To effectively use the available processing resources on multicore platforms, software designs should avoid co-executing applications or threads that can worsen the performance of shared caches, if not thrash them.While cache-aware scheduling techniques for such platforms have been proposed for throughput-oriented applications, to the best of our knowledge, no such work has targeted real-time applications. In this paper, we propose and evaluate a cache-aware Pfair-based scheduling scheme for real-time tasks on multicore platforms.