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Simultaneous Multithreading machines fetch and execute instructions from multiple instruction streams to increase system utilization and speedup the execution of jobs. When there are more jobs in the system than there is hardware to support simultaneous execution, the operating system scheduler must choose the set of jobs to coscheduleThis paper(More)
Scientific applications will have to scale to many thousands of processor cores to reach petascale. Therefore it is crucial to understand the factors that affect their scalability. Here we examine the strong scaling of four representative codes that exhibit different behaviors on four machines. We demonstrate the efficiency and analytic power of our(More)
SPECFEM3D_GLOBE is a spectral-element application enabling the simulation of global seismic wave propagation in 3D anelastic, anisotropic, rotating and self-gravitating Earth models at unprecedented resolution. A fundamental challenge in global seismology is to model the propagation of waves with periods between 1 and 2 seconds, the highest frequency(More)
The <i>Gordon</i> data intensive supercomputer entered service in 2012 as an allocable computing system in the NSF Extreme Science and Engineering Discovery Environment (XSEDE) program. <i>Gordon</i> has several innovative features that make it ideal for data intensive computing including: 1,024, compute nodes based on Intel's Sandy Bridge (Xeon E5)(More)
Cycle-accurate simulation is far too slow for modeling the expected performance of full parallel applications on large HPC systems. And just running an application on a system and observing wallclock time tells you nothing about why the application performs as it does (and is anyway impossible on yet-to-be-built systems). Here we present a framework for(More)
Simultaneous Multithreading machines benefit from jobscheduling software that monitors how well coscheduled jobs share CPU resources, and coschedules jobs that interact well to make more efficient use of those resources. As a result, informed coscheduling can yield significant performance gains over naive schedulers. However, prior work on coscheduling(More)
This paper presents a performance modeling methodology that is faster than traditional cycle-accurate simulation, more sophisticated than performance estimation based on system peak-performance metrics, and is shown to be effective on a class of High Performance Computing benchmarks. The method yields insight into the factors that affect performance on(More)