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000171880 037__ $$aFZJ-2014-05436
000171880 041__ $$aEnglish
000171880 1001_ $$0P:(DE-HGF)0$$aMao, Guoyong$$b0$$eCorresponding Author
000171880 1112_ $$aEuroMPI/ASIA 21st European MPI Users' Group Meeting$$cKyoto$$d2014-09-09 - 2014-09-12$$gEuroMPI/ASIA '14$$wJapan
000171880 245__ $$aCatching Idlers with Ease: A Lightweight Wait-State Profiler for MPI Programs
000171880 260__ $$aNew York, NY, USA$$bACM Press$$c2014
000171880 29510 $$aProceedings of the 21st European MPI Users' Group Meeting
000171880 300__ $$a6 p.
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000171880 520__ $$aLoad imbalance usually introduces wait states into the execution of parallel programs. Being able to identify and quantify wait states is therefore essential for the diagnosis and remediation of this phenomenon. An established method of detecting wait states is to generate event traces and compare relevant timestamps across process boundaries. However, large trace volumes usually prevent the analysis of longer execution periods. In this paper, we present an extremely lightweight wait-state profiler which does not rely on traces that can be used to estimate wait states in MPI codes with arbitrarily long runtimes. The profiler combines scalability with portability and low overhead.
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000171880 7001_ $$0P:(DE-HGF)0$$aBöhme, David$$b1
000171880 7001_ $$0P:(DE-HGF)0$$aHermanns, Marc-André$$b2
000171880 7001_ $$0P:(DE-Juel1)132112$$aGeimer, Markus$$b3$$ufzj
000171880 7001_ $$0P:(DE-HGF)0$$aLorenz, Daniel$$b4
000171880 7001_ $$0P:(DE-HGF)0$$aWolf, Felix$$b5
000171880 773__ $$a10.1145/2642769.2642783$$p103
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000171880 9101_ $$0I:(DE-588b)1026307295$$6P:(DE-HGF)0$$aGerman Research School for Simulation Sciences$$b1$$kGRS
000171880 9101_ $$0I:(DE-588b)1026307295$$6P:(DE-HGF)0$$aGerman Research School for Simulation Sciences$$b2$$kGRS
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000171880 9132_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bPOF III$$lKey Technologies$$vSupercomputing & Big Data $$x0
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