Global state detection using network preemption

Hori, Atsushi; Tezuka, Hiroshi; Ishikawa, Yutaka

doi:10.1007/3-540-63574-2_25

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…First, the master may limit the scalability of the system; since the master controls the timing of the global context-switch, the cost of a context-switch tends to increase with the scale of the system [Burger et al 1994;Ghormley et al 1989;Hori et al 1997]. Second, the master represents a single point-of-failure; while such a design may have been acceptable in a supercomputer where all components could be placed in a controlled environment, the operation of an entire cluster cannot depend on a single machine.…”

Section: Gang Schedulingmentioning

confidence: 99%

Implicit coscheduling

Arpaci-Dusseau

2001

ACM Trans. Comput. Syst.

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In modern distributed systems, coordinated time-sharing is required for communicating processes to leverage the performance of switch-based networks and low-overhead protocols. Coordinated time-sharing has traditionally been achieved with gang scheduling or explicit coscheduling, implementations of which often suffer from many deficiencies: multiple points of failure, high contextswitch overheads, and poor interaction with client-server, interactive, and I/O-intensive workloads. Implicit coscheduling dynamically coordinates communicating processes across distributed machines without these structural deficiencies. In implicit coscheduling, no communication is required across operating system schedulers; instead, cooperating processes achieve coordination by reacting to implicit information carried by communication existing within the parallel application. The implementation of this approach is simple and allows participating nodes to act autonomously. We introduce two key mechanisms in implicit coscheduling. The first is conditional two-phase waiting, a generalization of traditional two-phase waiting in which spin-time may be increased depending upon events occuring while the process waits. The second is an extension to stride scheduling that provides preemption and is fair to processes that block. To demonstrate that implicit coscheduling performs well, we show results from an extensive set of simulation and implementation experiments. To exercise the conditional two-phase waiting algorithm, we examine three workloads: bulk-synchronous and continuous-communication synthetic applications and application kernels written in the Split-C language. To exercise the local scheduler, we examine competing jobs with different communication characteristics. We demonstrate that our implementation scales well with the number of jobs and workstations and is robust to process placement. Our experiments show that implicit coscheduling is effective and fair for a wide range of workloads; most perform within 30% of an idealized model of gang scheduling.

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Section: Gang Schedulingmentioning

confidence: 99%

Implicit coscheduling

Arpaci-Dusseau

2001

ACM Trans. Comput. Syst.

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“…Specifically, several user-processes at a node could concurrently send a message and an incoming message is directly transferred by the NIC to the corresponding destination process at that node (even if that process is not currently scheduled). It is thus not necessary to perform network context switching when the processes are switched out on their respective CPUs, as was necessary [35], [13] until recently. Dynamic coscheduling strategies try to hypothesize what is scheduled at remote nodes using local events (messaging actions/events in particular) to guide the native operating system scheduler toward coscheduled execution whenever needed.…”

mentioning

confidence: 99%

Impact of workload and system parameters on next generation cluster scheduling mechanisms

Zhang

Sivasubramaniam

Moreira

et al. 2001

IEEE Trans. Parallel Distrib. Syst.

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AbstractÐScheduling of processes onto processors of a parallel machine has always been an important and challenging area of research. The issue becomes even more crucial and difficult as we gradually progress to the use of off-the-shelf workstations, operating systems, and high bandwidth networks to build cost-effective clusters for demanding applications. Clusters are gaining acceptance not just in scientific applications that need supercomputing power, but also in domains such as databases, web service, and multimedia which place diverse Quality-of-Service (QoS) demands on the underlying system. Further, these applications have diverse characteristics in terms of their computation, communication, and I/O requirements, making conventional parallel scheduling solutions, such as space sharing or gang scheduling, unattractive. At the same time, leaving it to the native operating system of each node to make decisions independently can lead to ineffective use of system resources whenever there is communication. Instead, an emerging class of dynamic coscheduling mechanisms that attempt to take remedial actions to guide the system toward coscheduled execution without requiring explicit synchronization offers a lot of promise for cluster scheduling. Using a detailed simulator, this paper evaluates the pros and cons of different dynamic coscheduling alternatives while comparing their advantages over traditional gang scheduling (and not performing any coordinated scheduling at all). The impact of dynamic job arrivals, job characteristics, and different system parameters on these alternatives is evaluated in terms of several performance criteria. In addition, heuristics to enhance one of the alternatives even further are identified, classified, and evaluated. It is shown that these heuristics can significantly outperform the other alternatives over a spectrum of workload and system parameters and is thus a much better option for clusters than conventional gang scheduling.

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