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A. C. Sodan 《Concurrency and Computation》2005,17(15):1725-1781
Loosely coordinated (implicit/dynamic) coscheduling is a time‐sharing approach that originates from network of workstations environments of mixed parallel/serial workloads and limitedsoftware support. It is meant to be an easy‐to‐implement and scalable approach. Considering that the percentage of clusters in parallel computing is increasing and easily portable software is needed, loosely coordinated coscheduling becomes an attractive approach for dedicated machines. Loose coordination offers attractive features as a dynamic approach. Static approaches for local job scheduling assign resources exclusively and non‐preemptively. Such approaches still remain beyond the desirable resource utilization and average response times. Conversely, approaches for dynamic scheduling of jobs can preempt resources and/or adapt their allocation. They typically provide better resource utilization and response times. Existing dynamic approaches are full preemption with checkpointing, dynamic adaptation of node/CPU allocation, and time sharing via gang or loosely coordinated coscheduling. This survey presents and compares the different approaches, while particularly focusing on the less well‐explored loosely coordinated time sharing. The discussion particularly focuses on the implementation problems, in terms of modification of standard operating systems, the runtime system and the communication libraries. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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A. Sodan V. Torra 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2001,5(1):77-92
With applications currently growing in complexity and range, increasing numbers of configuration problems are arising in
compilers. Already many software systems offer multiple specialized implementation strategies and substrategies, differing
in terms of applicability and/or cost, depending on the application context. Configurations then have to be created from the
different strategies available in accordance with the application characteristics, the global optimization objective, and
potential constraints on the strategies' combinability. In many cases, this results in a combinatorial, i.e., discrete, optimization
problem. Proper solutions for automating the configuration while limiting the complexity of the solution search are still
being sought. We address here the field of parallel/distributed processing and the configuration of runtime implementation
strategies, such as for communication or dynamic load balancing. We present a rule-based approach, integrating fuzzy methodologies
for the classification of application characteristics and for gradual selection preference in rules. In this way we exploit
available knowledge about the correlation of the problem and solution space, and apply soft computing methods to obtain an
approximate, rather than perfect, solution approach, thus helping to limit the configuration complexity. Our approach extends
standard fuzzy inference by a multistage organization, and – with proper organization of rules, characteristics and strategies
– performs hierarchical fuzzy inference. The approach is demonstrated on concrete configuration examples in parallel compilers. 相似文献
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Job scheduling typically focuses on the CPU with little work existing to include I/O or memory. Time-shared execution provides the chance to hide I/O and long-communication latencies though potentially creating a memory conflict. Hyperthreaded CPUs support coscheduling without any context switches and provide additional options for CPU-internal resource sharing. We present an approach that includes all possible resources into the schedule optimization and improves utilization by coscheduling two jobs if feasible. Our LOMARC approach partially reorders the queue by lookahead to increase the potential to find good matches. In simulations based on the workload model of Lublin and Feitelson, we have obtained improvements between 30 percent and 50 percent in both response times and relative bounded response times on hyperthreaded CPUs (i.e., cut times to two third or to half) 相似文献
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