Real-time scheduling algorithms for multiprocessor systems have been the subject of considerable recent interest. For such an algorithm to be truly useful in practice, support for semaphore-based locking must be provided. However, for many global scheduling algorithms, no such mechanisms have been proposed. Furthermore, in the partitioned case, most prior semaphore schemes are either inefficient or restrict critical sections considerably. In this paper, a new flexible multiprocessor locking scheme is presented that can be applied under both partitioning and global scheduling. This scheme allows unrestricted critical-section nesting, but has been designed to deal with the common case of short non-nested accesses efficiently.

When locking protocols are used in real-time systems, bounds on blocking times are required when ensuring timing constraints. While the term "blocking" is well-understood in the context of uniprocessor real-time systems, the same is not true in the multiprocessor case. In this paper, two definitions of blocking are presented that are applicable to suspensionbased multiprocessor locking protocols. The need for two definitions arises because of differences in how suspensions are handled in existing schedulability analysis. For each definition, locking protocols are presented that have asymptotically optimal blocking behavior. In particular, protocols are presented for any job-level static-priority global or partitioned scheduling algorithm.

Multicore platforms are predicted to become significantly larger in the coming years. Given that real-time workloads will inevitably be deployed on such platforms, the scalability of the scheduling algorithms used to support such workloads warrants investigation. In this paper, this issue is considered and an empirical evaluation of several global and partitioned scheduling algorithms is presented. This evaluation was conducted using a Sun Niagara multicore platform with 32 logical CPUs (eight cores, four hardware threads per core). In this study, each tested algorithm proved to be a viable choice for some subset of the workload categories considered.

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Abstract. In general computing systems, a job (process/task) may suspend itself whilst it is waiting for some activity to complete, e.g., an accelerator to return data. In real-time systems, such self-suspension can cause substantial performance/schedulability degradation. This observation, first made in 1988, has led to the investigation of the impact of self-suspension on timing predictability, and many relevant results have been published since. Unfortunately, as it has recently come to light, a number of the existing results are flawed. To provide a correct platform on which future research can be built, this paper reviews the state of the art in the design and analysis of scheduling algorithms and schedulability tests for self-suspending tasks in real-time systems. We provide (1) a systematic description of how self-suspending tasks can be handled in both soft and hard real-time systems; (2) an explanation of the existing misconceptions and their potential remedies; (3) an assessment of the influence of such flawed analyses on partitioned multiprocessor fixed-priority scheduling when tasks synchronize access to shared resources; and (4) a discussion of the computational complexity of analyses for different self-suspension task models.