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Towards no-cost adaptive mpsoc static schedules through exploitation of logical-to-physical core mapping latitude
- In Design, Automation Test in Europe Conference Exhibition, 2009. DATE ’09
, 2009
"... Abstract—The computing engines of many current applications are powered by MPSoC platforms, which promise significant speedup but induce increased reliability problems as a result of ever growing integration density and chip size. While static MPSoC execution schedules deliver predictable worst-case ..."
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Abstract—The computing engines of many current applications are powered by MPSoC platforms, which promise significant speedup but induce increased reliability problems as a result of ever growing integration density and chip size. While static MPSoC execution schedules deliver predictable worst-case per-formance, the absence of dynamic variability unfortunately con-strains their usefulness in such an unreliable execution environ-ment. Adaptive static schedules with predictable responses to run-time resource variations have consequently been proposed, yet the extra constraints imposed by adaptivity on task assignment have resulted in schedule length increases. We propose to eradicate the associated performance degradation of such techniques while retaining all the concomitant benefits, by exploiting an inherent degree of freedom in task assignment regarding the logical to physical core mapping. The proposed technique relies on the use of core reordering and rotation through utilizing a graph representation model, which enables a direction translation of inter-core communication paths into order requirements between cores. The algorithmic implementation results confirm that the proposed technique can drastically reduce the schedule length overhead of both pre- and post- reconfiguration schedules. I.
A task remapping technique for reliable multi-core embedded systems
- In CODES+ISSS
, 2010
"... With the continuous scaling of semiconductor technology, the life-time of circuit is decreasing so that processor failure becomes an important issue in MPSoC design. A software solution to tolerate run-time processor failure is to migrate tasks from the failed processors to the live processors when ..."
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With the continuous scaling of semiconductor technology, the life-time of circuit is decreasing so that processor failure becomes an important issue in MPSoC design. A software solution to tolerate run-time processor failure is to migrate tasks from the failed processors to the live processors when failure occurs. Previous works on run-time task migration usually aim to minimize the migration overhead with or without a given latency constraint. For streaming applications, however, it is more important to minimize the throughput degradation than the migration overhead or the latency. Hence, we propose a task remapping technique to minimize the throughput degradation assuming that the migration overhead can be amortized safely. The target multi-core system assumed in this paper consists of processor pools and each pool consists of homogeneous processors. The proposed technique is based on an intensive compile-time analysis for all possible failure scenarios. It involves the following steps; 1) Determine the static mapping of tasks onto the live processors, aiming to minimize the throughput degradation: 2) Find an optimal processor-to-processor mapping to minimize the task migration overhead: and 3) Store the resultant task remapping information that includes task mapping and processor-to-processor mapping results. Since the task remapping information is pre-computed at compile-time for all possible failure scenarios, it should be efficiently represented and stored. At run-time, we simply remap the tasks following the compile-time decision. We examine the scalability of the proposed technique on both space and run-time overhead for compile-time analysis varying the number of failed processors. Through intensive experiments, we show that the proposed technique outperforms the previous works with respect to application throughput.
A decentralized strategy for genetic scheduling in heterogeneous environments, Multiagent Grid Syst
, 2007
"... Abstract. The paper describes a solution to the key problem of en-suring high performance behavior of the Grid, namely the scheduling of activities. It presents a distributed, fault-tolerant, scalable and efficient solution for optimizing task assignment. The scheduler uses a combina-tion of genetic ..."
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Abstract. The paper describes a solution to the key problem of en-suring high performance behavior of the Grid, namely the scheduling of activities. It presents a distributed, fault-tolerant, scalable and efficient solution for optimizing task assignment. The scheduler uses a combina-tion of genetic algorithms and lookup services for obtaining a scalable and highly reliable optimization tool. The experiments have been car-ried out on the MonALISA monitoring environment and its extensions. The results demonstrate very good behavior in comparison with other scheduling approaches.
Realistic Models and Efficient Algorithms for Fault Tolerant Scheduling on Heterogeneous Platforms
, 2008
"... Most list scheduling heuristics rely on a simple platform model where communication contention is not taken into account. In addition, it is generally assumed that processors in the systems are completely safe. To schedule precedence graphs in a more realistic framework, we introduce an efficient fa ..."
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Cited by 4 (4 self)
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Most list scheduling heuristics rely on a simple platform model where communication contention is not taken into account. In addition, it is generally assumed that processors in the systems are completely safe. To schedule precedence graphs in a more realistic framework, we introduce an efficient fault tolerant scheduling algorithm that is both contentionaware and capable of supporting ε arbitrary fail-silent (fail-stop) processor failures. We focus on a bi-criteria approach, where we aim at minimizing the total execution time, or latency, given a fixed number of failures supported in the system. Our algorithm has a low time complexity, and drastically reduces the number of additional communications induced by the replication mechanism. Experimental results fully demonstrate the usefulness of the proposed algorithm, which leads to efficient execution schemes while guaranteeing a prescribed level of fault tolerance.
Scheduling in multi-processor system using genetic algorithms
- In Proceedings of the Genetic Engineering and Evolutionary Computation Conference
, 2005
"... Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such co ..."
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Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. This paper investigates dynamic scheduling of real-time tasks in a multiprocessor system to obtain a feasible solution using genetic algorithms combined with well-known heuristics, such as ‘Earliest Deadline First ’ and ‘Shortest Computation Time First’. A comparative study of the results obtained from simulations shows that genetic algorithm can be used to schedule tasks to meet deadlines, in turn to obtain high processor utilization. 1.
Fault-Tolerant Scheduling in Homogeneous Real-Time Systems
"... Real-time systems are one of the most important applications of computers, both in commercial terms and in terms of social impact. Increasingly, real-time computers are used to control life-critical applications and need to meet stringent reliability conditions. Since the reliability of a real-time ..."
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Cited by 2 (0 self)
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Real-time systems are one of the most important applications of computers, both in commercial terms and in terms of social impact. Increasingly, real-time computers are used to control life-critical applications and need to meet stringent reliability conditions. Since the reliability of a real-time system is related to the probability of meeting its hard deadlines, these reliability requirements translate to the need to meet critical task deadlines with a very high probability. We survey the problem of how to schedule tasks in such a way that deadlines continue to be met despite processor (permanent or transient) or software failure.
Teaching Real-Time with a scheduler simulator
, 2001
"... In this paper we describe a scheduler simulator for real-time tasks, RTsim, that can be used as a tool to teach real-time scheduling algorithms. It simulates a variety of preprogrammed scheduling policies for single and multiprocessor systems and simple algorithm variants introduced by its user. Usi ..."
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In this paper we describe a scheduler simulator for real-time tasks, RTsim, that can be used as a tool to teach real-time scheduling algorithms. It simulates a variety of preprogrammed scheduling policies for single and multiprocessor systems and simple algorithm variants introduced by its user. Using RTsim students can conduct experiments that will allow them to understand the effects of each policy given different load conditions and learn which policy is better for different workloads. We show how to use RTsim as a learning tool and the results achieved with its application on the Real-Time Systems course taught at the B.Sc. on Computer Science at Paulista State University - Unesp - at Rio Preto.
Multi-Criteria Scheduling of Precedence Task Graphs on Heterogeneous Platforms
- The Computer J
, 2010
"... Latency, fault tolerance and reliability are important requirements for several applications that are time critical in nature: such applications require guarantees in terms of latency, even when processors are subject to failures. In this paper, we propose a fault-tolerant scheduling heuristic for m ..."
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Latency, fault tolerance and reliability are important requirements for several applications that are time critical in nature: such applications require guarantees in terms of latency, even when processors are subject to failures. In this paper, we propose a fault-tolerant scheduling heuristic for mapping precedence task graphs on heterogeneous systems. Our approach is based on an active replication scheme, capable of supporting ε arbitrary fail-silent/fail-stop processor failures, and hence valid results will be provided even if ε processors fail. First we focus on a bi-criteria approach, where we aim at minimizing the latency given a fixed number of failures supported in the system, or the other way round. Next we derive a more complex algorithm in which we not only minimize latency and support a fixed number of failures, but also improve the overall reliability. Major achievements include low complexity of the new algorithms, and a drastic reduction of the number of additional communications induced by the replication mechanism. Experimental results demonstrate that our heuristics, despite their lower complexity, outperform their direct competitor, the fault-tolerance based active replication scheduling algorithm FTBAR.
A Fault Tolerant Scheduling Algorithm for DAG Applications in Cluster Environments.
- In: International Conference on Digital Information Processing and Communication, Springer-CCIS,
, 2011
"... Abstract. Fault tolerance is an essential requirement in systems running applications which need a technique to continue execution where some system components are subject to failure. In this paper, a fault tolerant task scheduling algorithm is proposed for mapping task graphs to heterogeneous proc ..."
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Abstract. Fault tolerance is an essential requirement in systems running applications which need a technique to continue execution where some system components are subject to failure. In this paper, a fault tolerant task scheduling algorithm is proposed for mapping task graphs to heterogeneous processing nodes in cluster computing systems. The starting point of the algorithm is a DAG representing an application with information about the tasks. This information consists of the execution time of the tasks on the target system processors, communication times between the tasks having data dependencies, and the number of the processor failures (ε) which should be tolerated by the scheduling algorithm. The algorithm is based on the active replication scheme, and it schedules ε+1 replicas of each task to achieve the required fault tolerance. Simulation results show the efficiency of the proposed algorithm in spite of its lower complexity.
Preference-oriented scheduling framework and its application in fault-tolerant real-time systems (extended version
, 2012
"... Abstract—In fault-tolerant systems, the primary and backup copies of different tasks can be scheduled together on one processor, where primary tasks should be executed as soon as possible (ASAP) and backup tasks as late as possible (ALAP) for better performance (e.g., energy efficiency). To address ..."
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Abstract—In fault-tolerant systems, the primary and backup copies of different tasks can be scheduled together on one processor, where primary tasks should be executed as soon as possible (ASAP) and backup tasks as late as possible (ALAP) for better performance (e.g., energy efficiency). To address such mixed requirements, in this paper, we propose the concept of preference-oriented execution and study the corresponding scheduling algorithms. Specifically, we formally define the optimality of preference-oriented schedules and show that such schedules may not always exist for general periodic task sets. Then, we propose an ASAP-Ensured Earliest Deadline (SEED) scheduling algorithm, which guarantees to generate an ASAPoptimal schedule for any schedulable task set. Moreover, to incorporate the preference for ALAP tasks, we extend SEED and develop a Preference-Oriented Earliest Deadline (POED) scheduling heuristic. For a dual-processor fault-tolerant system, we illustrate how such algorithms can be exploited to improve the energy savings. We evaluate the proposed schedulers through extensive simulations. The results confirm the optimality of SEED for ASAP tasks. When compared to the well-known EDF scheduler, both SEED and POED can perform better in preferenceoriented settings with reasonable overheads. Moreover, for a dualprocessor fault-tolerant system, significant energy savings (up to 20%) can be obtained under POED when compared to the stateof-the-art standby-sparing scheme.
