Large‐Scale Computing 2011
DOI: 10.1002/9781118130506.ch3
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Accelerated Many‐Core GPU Computing for Physics and Astrophysics on Three Continents

Abstract: PrefaceTo be completed.Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of the book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems … Show more

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Cited by 4 publications
(5 citation statements)
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“…This issue was found to be of minor importance in the simulations with higher spatial resolution (and, hence, lower surface/volume ratio). For example, for the 128-GPU benchmark on the Laohu GPU cluster at NAOC, the MPI communication time takes less than 2% of the total execution time (Spurzem et al 2011). Also note that this issue can potentially be largely alleviated by overlapping communication with computation.…”
Section: Amr Performancementioning
confidence: 99%
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“…This issue was found to be of minor importance in the simulations with higher spatial resolution (and, hence, lower surface/volume ratio). For example, for the 128-GPU benchmark on the Laohu GPU cluster at NAOC, the MPI communication time takes less than 2% of the total execution time (Spurzem et al 2011). Also note that this issue can potentially be largely alleviated by overlapping communication with computation.…”
Section: Amr Performancementioning
confidence: 99%
“…In astrophysical simulations, considerable performance speed-ups in multi-GPU systems have been demonstrated in a broad range of applications, for example, the direct N -body simulations (e.g. Schive et al 2008; Gaburov et al 2009; Spurzem et al 2011), Barnes–Hut tree algorithm (Hamada et al 2009), reionization simulations (Aubert and Teyssier 2010), adaptive mesh refinement (AMR; Schive et al 2010; Wang et al 2010), general relativistic magnetohydrodynamics (MHD) (Zink 2011), and interactive visualization of large 3D astronomical data (Hassan et al 2011).…”
Section: Introductionmentioning
confidence: 99%
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“…They are used to accelerate many scientific calculations, especially in astrophysics, such as the dynamics of dense star clusters and galaxy centers (see review by Spurzem et al 2012). The main issue when implementing a mathematical technique for GPUs is to make the algorithm parallel.…”
Section: Methodsmentioning
confidence: 99%
“…The code is designed to use different softening parameters for the gravity calculation (if it is required) for different astrophysical components in our simulations like SMBHs, dark matters or stars particles. More details about the ϕ−GPU code public version and its performance are presented in (Spurzem et al 2012;Berczik et al 2013). The present code is well tested and has already been used to obtain important results in our earlier large scale simulations (up to few million bodies) (Wang et al 2014;Zhong et al 2014;Li et al 2012Li et al , 2017.…”
Section: ϕ−Gpu Codementioning
confidence: 99%