Pfair Scheduling was proposed by... In this paper, we introduce a work-conserving variant of Pfair scheduling called "early-release" fair (ERfair) scheduling. We also present a new scheduling algorithm called PD² and show that it is optimal for scheduling any mix of early-release and non-early-release asynchronous, periodic tasks. In contrast, almost all prior work on Pfair scheduling has been limited to synchronous systems. PD²is an optimization of an earlier deadline-based algorithm of Baruah, Gehrke, and Plaxton called PD; PD² uses a simpler tie-breaking scheme than PD to disambiguate equal deadlines. We present a series of counterexamples that suggest that, in general, the PD² tie-breaking mechanism cannot be simplified. In contrast to this, we show that no tie-breaking information is needed on two-processor systems.

We consider the intra-sporadic task model, which is a generalization of the sporadic task model motivated by recent work on Pfair scheduling. The intra-sporadic model is essentially a quantum-based, multiprocessor variant of the uniprocessor rate-based execution model of Jeffay and Goddard. In the intra-sporadic model, a task is specified by an average rate of execution, and there is no restriction on instantaneous execution rates. Such exibility is useful in applications in which some processing steps may be highly jittered. In previous work, we showed that an intra-sporadic task system is feasible on M processors i its total utilization is at most M . We also gave an optimal algorithm for scheduling intra-sporadic tasks on two processors. In this paper, we show that the PD² Pfair algorithm can be used to schedule any intra-sporadic task system that is feasible on M processors. Because the sporadic model is a special case of the intrasporadic model, our work shows that PD² is also optimal for scheduling sporadic tasks on a multiprocessor. This paper is the first to show that sporadic or intra-sporadic tasks can be optimally scheduled on systems of more than two processors.

In this paper, we consider variants of Pfair and ERfair scheduling in which subtasks may be released late, i.e., there may be separation between consecutive windows of the same task. We call such tasks intra-sporadic tasks. There are two main contributions of this paper. First, we show the existence of a Pfair (and hence ERfair) schedule for any intra-sporadic task system whose utilization is at most the number of available processors. Second, we give a polynomial-time algorithm that is optimal for scheduling intra-sporadic tasks in a Pfair or ERfair manner on systems of one or two processors.

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In soft real-time applications, tasks are allowed to miss their deadlines. Thus, less-costly scheduling algorithms can be used at the price of occasional violations of timing constraints. This may be acceptable if reasonable tardiness bounds (i.e., bounds on the extent to which deadlines may be missed) can be guaranteed. In this paper, we consider soft real-time applications implemented on multiprocessors. Pfair scheduling algorithms are the only known means of optimally scheduling hard real-time applications on multiprocessors. For this reason, we consider the use of such algorithms here. In the design of Pfair scheduling algorithms, devising schemes to correctly break ties when several tasks have the same deadline is a critical issue. Such tie-breaking schemes entail overhead that may be unacceptable or unnecessary in soft real-time applications. In this paper, we consider the earliest pseudo-deadline first (EPDF) Pfair algorithm, which avoids this overhead by using no tie-breaking information. Our main contributions are twofold. First, we establish a condition for ensuring a tardiness of at most one quantum under EPDF. This condition is very liberal and should often hold in practice. Second, we present simulation results involving randomly-generated task sets, including those that do not satisfy our condition. In these experiments, deadline misses rarely occurred, and no misses by more than one quantum ever occurred. ∗ Work supported by NSF grants CCR 9972211, CCR 9988327, ITR 0082866, and CCR 0204312. 1

We consider the "supertask" approach, proposed by Moir and Ramamurthy at RTSS '99 as means for supporting non-migratory tasks in Pfair-scheduled systems. In this approach, tasks bound to the same processor are combined into a single supertask, which is scheduled as an ordinary Pfair task; when a supertask is scheduled, one of its component tasks is selected for execution. Unfortunately, while Moir and Ramamurthy's paper suggests that supertasking is a promising approach, counterexamples presented by them show that non-migratory tasks can actually miss their deadlines when supertasking is used in conjunction with all known Pfair scheduling algorithms. In this paper, we show that such deadline misses can be prevented by inflating each supertask's utilization. We present experimental evidence that shows that the required inflation factors should be small in practice. We also show that these ination factors usually can be reduced if, instead of being scheduled in a Pfair manner, non-migratory tasks are scheduled (perhaps "unfairly") using earliest-deadline-first priorities. In soft-real-time and rate-based systems, it may be permissible for a task to miss a deadline by a small amount. We show that our ination factors also can be reduced if this is the case.

Partitioning and global scheduling are two approaches for scheduling real-time tasks on multiprocessors. Though partitioning is sub-optimal it has traditionally been preferred; this is mainly due to the fact that well-understood uniprocessor scheduling algorithms can be used on each processor. In recent years, global scheduling algorithms based on the concept of "proportionate fairness" (Pfairness)have received considerabl attention. Pfairal)[[2#3) are of interest because they are currentl the onl known method for optimal) schedul13 periodic, sporadic, and "rate-based" task systems on mul6[]2 cessors. In addition, there has been growing practical interest in schedul32 with fairness guarantees. However, the frequency of context switching and migration in Pfair-scheduls systems has l) to some questions concerning the practicalR y of Pfair schedul#6) In this paper, we investigate this issue by comparing the PD Pfairalir)2B1 to the EDF-FF partitioning scheme, which uses "first fit" (FF)as a partitioning heuristic and theearlBB):[B2B1)l first (EDF)al):R3R# for per-processor schedul1): We present experimental resul) that show that is competitive with, and in some cases outperforms, EDF-FF. These resulL suggest that Pfair schedulR) is aviabl all1):R] e to partitioning. Furthermore, as discussed herein, Pfair scheduling provides many additional benefits, such assimpl and efficient synchronization, temporal isolL1]): faul tol1]):R6 and support for dynamic tasks.

We are entering the multi-core era in computer science. All major high-performance processor manufacturers have integrated at least two cores (processors) on the same chip — and it is predicted that chips with many more cores will become widespread in the near future. As cores on the same chip share the DRAM memory system, multiple programs executing on different cores can interfere with each others ’ memory access requests, thereby adversely affecting one another’s performance. In this paper, we demonstrate that current multi-core processors are vulnerable to a new class of Denial of Service (DoS) attacks because the memory system is “unfairly ” shared among multiple cores. An application can maliciously destroy the memory-related performance of another application running on the same chip. We call such an application a memory performance hog (MPH). With the widespread deployment of multi-core systems in commodity desktop and laptop computers, we expect MPHs to become a prevalent security issue that could affect almost all computer users. We show that an MPH can reduce the performance of another application by 2.9 times in an existing dual-core system, without being significantly slowed down itself; and this problem will become more severe as more cores are integrated on the same chip. Our analysis identifies the root causes of unfairness in the design of the memory system that make multi-core processors vulnerable to MPHs. As a solution to mitigate the performance impact of MPHs, we propose a new memory system architecture that provides fairness to different applications running on the same chip. Our evaluations show that this memory system architecture is able to effectively contain the negative performance impact of MPHs in not only dual-core but also 4-core and 8-core systems. 1

The goal of this dissertation is to extend the Pfair scheduling approach in order to enable its efficient implementation on a real-time multiprocessor. At present, Pfair scheduling is the only known means for optimally scheduling recurrent real-time tasks on multiprocessors. In addition, there has been growing practical interest in such approaches due to their fairness guarantees. Unfortunately, prior work in this area has considered only the scheduling of independent tasks, which do not communicate with each other or share resources. The work presented herein focuses both on adding support for these actions and also on developing techniques for reducing various forms of implementation overhead, including that produced by task migrations and context switches. The thesis of this dissertation is: tasks can be efficiently synchronized in Pfair-scheduled systems and overhead due to common system events, such as context switches and migrations, can be reduced. This thesis is established through research in three areas. First, the pre-existing Pfair schedul- ing theory is extended to support the scheduling of groups of tasks as a single entity. Second, mechanisms for supporting both lock-based and lock-free synchronization are presented. Lock- based synchronization coordinates access to shared resources through the use of semaphores. On the other hand, lock-free operations are optimistically attempted and then retried if the operation fails. Last, the deployment of Pfair scheduling on a symmetric multiprocessor is considered.

We consider various techniques for implementing shared objects and for accounting for objectsharing overheads in Pfair-scheduled multiprocessor systems. We primarily focus on the use of lock-free objects, though some lock-based alternatives are briefly considered as well. Lock-free objects are more economical for implementing relatively simple objects such as buffers, stacks, queues, and lists; locking techniques are preferable for more complicated objects and for sychronizing accesses to physical devices. We present schedulability conditions for Pfair-scheduled systems in which lock-free objects are used. In addition, using shared queues as an example, we show how one can exploit the tight synchrony that exists in Pfair-scheduled systems to optimize lock-free implementations. We also show that lock-free object-sharing overheads can be reduced by combining tasks into supertasks; this is because, within a supertask, less-costly uniprocessor synchronization techniques can be used.