Aerodynamic Analysis of Complex Missile Configurations Using AVUS (Air Vehicles Unstructured Solver)

Hoke, Charles M.; Burnley, V.; Schwabacher, G.

doi:10.2514/6.2004-5452

Cited by 9 publications

(3 citation statements)

References 1 publication

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“…Figure 5 illustrates the hit rate coverage for MultiMAPS and a set of real applications in terms of hit rate bins based on simulation of an Opteron processor. The applications are Hycom [9], Avus [10] and Overflow2 [11] from the Department of Defense TI-07 benchmarks suite [7]. Each point in Figure 5 indicates whether a bin includes one or more hit rate tuples that correspond to the bin.…”

Section: Hit Rate Coverage Of Multimapsmentioning

confidence: 99%

A genetic algorithms approach to modeling the performance of memory-bound computations

Tikir

Carrington

Strohmaier

et al. 2007

Proceedings of the 2007 ACM/IEEE Conference on Supercomputing

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Benchmarks that measure memory bandwidth, such as STREAM, Apex-MAPS and MultiMAPS, are increasingly popular due to the "Von Neumann" bottleneck of modern processors which causes many calculations to be memory-bound. We present a scheme for predicting the performance of HPC applications based on the results of such benchmarks. A Genetic Algorithm approach is used to "learn" bandwidth as a function of cache hit rates per machine with MultiMAPS as the fitness test. The specific results are 56 individual performance predictions including 3 full-scale parallel applications run on 5 different modern HPC architectures, with various CPU counts and inputs, predicted within 10% average difference with respect to independently verified runtimes.

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Section: Hit Rate Coverage Of Multimapsmentioning

confidence: 99%

A genetic algorithms approach to modeling the performance of memory-bound computations

Tikir

Carrington

Strohmaier

et al. 2007

Proceedings of the 2007 ACM/IEEE Conference on Supercomputing

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“…Production applications include HYCOM [Chassignet et al 2007], AVUS [Hoke et al 2004], LAMMPS [Plimpton et al 2007], ICEPIC [Mardahl et al 2003], and CTH [Davis et al 2007]. The microbenchmarks include a number of kernels from pcubed [Laurenzano et al 2011] and polybench [Pouchet 2012].…”

Section: Application Codesmentioning

confidence: 99%

Making the Most of SMT in HPC

Porter

Laurenzano

Tiwari

et al. 2015

ACM Trans. Archit. Code Optim.

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This work presents an end-to-end methodology for quantifying the performance and power benefits of simultaneous multithreading (SMT) for HPC centers and applies this methodology to a production system and workload. Ultimately, SMT's value system-wide depends on whether users effectively employ SMT at the application level. However, predicting SMT's benefit for HPC applications is challenging; by doubling the number of threads, the application's characteristics may change. This work proposes statistical modeling techniques to predict the speedup SMT confers to HPC applications. This approach, accurate to within 8%, uses only lightweight, transparent performance monitors collected during a single run of the application.

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“…However, even before enabling OpenMP, these new BG/P run modes broaden the applications range of the BG/P system significantly beyond that available to the BG/L system. Two specific applications that illustrate this point are CTH [22] and AVUS [23]. CTH is an application from Sandia National Laboratory for modeling complex multidimensional, multimaterial problems.…”

Section: Bg/p Application Performance and Scalingmentioning

confidence: 99%

Overview of the IBM Blue Gene/P project

2008

IBM J. Res. & Dev.

119

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Aerodynamic Analysis of Complex Missile Configurations Using AVUS (Air Vehicles Unstructured Solver)

Cited by 9 publications

References 1 publication

A genetic algorithms approach to modeling the performance of memory-bound computations

A genetic algorithms approach to modeling the performance of memory-bound computations

Making the Most of SMT in HPC

Overview of the IBM Blue Gene/P project

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