System Characteristics and Performance Analysis in Multi and Many-core Architectures

Yoon, JunWeon; Song, Ui-Sung

doi:10.9728/dcs.2019.20.3.597

Cited by 2 publications

(1 citation statement)

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“…Butcher et al (2018) studied optimization methods for data types that are not suitable for MCDRAM on a KNL system [4]. discussed a solution for performance bottlenecks that can occur when running MPI applications on a KNL system [5], and Yoon and Song (2019) analyzed the features of manycore architectures such as the KNL system [6]. However, these studies were not conducted using general numerical models used in real circumstances and did not include the effects of inputs and outputs.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparisons on Parallel Optimization of Atmospheric and Ocean Numerical Circulation Models Using KISTI Supercomputer Nurion System

et al. 2020

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The characteristics of the 5th Supercomputer Nurion Knights Landing (KNL) system of the Korea Institute of Science and Technology Information (KISTI) were analyzed by developing ultra-high resolution atmospheric and ocean numerical circulation models. These models include the Weather Research and Forecasting System (WRF), Regional Ocean Modeling System (ROMS), and Unstructured Grid Finite Volume Community Ocean Model (FVCOM). Ideal and real-case experiments were simulated for each model according to the number of parallelized cores used for comparing performances. Identical experiments were performed on a general multicore system (Skylake and a general cluster system) for a performance comparison with the Nurion KNL system. Although the KNL system has more than twice as many cores per node as the Skylake system, the KNL system demonstrated 1/3 of the performance rate of the Skylake system. However, the performance rate of the Nurion KNL system was approximately 43% for all experiments. Reducing the number of cores per node in the KNL system by half (36 cores) is the most efficient method when the total number of cores is less than 256 cores, while it is more economical to use all cores when using more than 256 cores. In all experiments, the performance was continuously improved even for a maximum core experiment (1024 cores), thereby indicating that the KNL system can effectively simulate ultra-high resolution numerical circulation models.

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Section: Introductionmentioning

confidence: 99%