000129700 001__ 129700
000129700 005__ 20190404060236.0
000129700 0247_ $$a10.1016/j.jcss.2007.07.003$$2doi
000129700 02470 $$2ISI$$a000258791600004
000129700 02470 $$a10.1016/j.jcss.2007.07.003$$2DOI
000129700 037__ $$aARTICLE
000129700 245__ $$aA simulator for adaptive parallel applications
000129700 269__ $$a2007
000129700 260__ $$c2007
000129700 336__ $$aJournal Articles
000129700 520__ $$aDynamically allocating computing nodes to parallel applications is a promising technique for improving the utilization of cluster resources. Detailed simulations can help identify allocation strategies and problem decomposition parameters that increase the efficiency of parallel applications. We describe a simulation framework supporting dynamic node allocation which, given a simple cluster model, predicts the running time of parallel applications taking CPU and network sharing into account. Simulations can be carried out without needing to modify the application code. Thanks to partial direct execution, simulation times and memory requirements are reduced. In partial direct execution simulations, the application's parallel behavior is retrieved via direct execution, and the duration of individual operations is obtained from a performance prediction model or from prior measurements. Simulations may then vary cluster model parameters, operation durations and problem decomposition parameters to analyze their impact on the application performance and identify the limiting factors. We implemented the proposed techniques by adding direct execution simulation capabilities to the Dynamic Parallel Schedules parallelization framework. We introduce the concept of dynamic efficiency to express the resource utilization efficiency as a function of time. We verify the accuracy of our simulator by comparing the effective running time, respectively the dynamic efficiency, of parallel program executions with the running time, respectively the dynamic efficiency, predicted by the simulator under different parallelization and dynamic node allocation strategies.
000129700 6531_ $$aAdaptive
000129700 6531_ $$aparallel
000129700 6531_ $$aapplication
000129700 6531_ $$asimulation
000129700 6531_ $$aDynamic
000129700 6531_ $$aefficiency
000129700 6531_ $$aSensitivity
000129700 6531_ $$aanalysis
000129700 6531_ $$aPartial
000129700 6531_ $$adirect
000129700 6531_ $$aexecution
000129700 700__ $$g114320$$aSchaeli, B.$$0240888
000129700 700__ $$g101589$$aGerlach, S.$$0240940
000129700 700__ $$g105390$$aHersch, R.D.$$0242314
000129700 773__ $$j74$$tJournal of Computer and System Sciences$$k6$$q983-999
000129700 8560_ $$falain.borel@epfl.ch
000129700 909C0 $$xU10417$$0252034$$pLSP
000129700 909CO $$pIC$$particle$$ooai:infoscience.tind.io:129700
000129700 937__ $$aLSP-ARTICLE-2008-008
000129700 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000129700 980__ $$aARTICLE