Abstract:

Mechanisms of interactions among different scale phenomena play important roles for forecasting of weather and climate. Multi-scale Simulator for the Geoenvironment (MSSG), which deals with multi-scale multi-physics phenomena, is a coupled non-hydrostatic atmosphere-ocean model designed to be run efficiently on the Earth Simulator. We present its simulation results with the world-highest 1.9km horizontal resolution for the entire globe. To gain high performance by exploiting the system capabilities, we propose novel performance evaluation metrics that incorporate the effects of the data caching mechanism between CPU and memory. A potentially attainable computational performance is also introduced by evaluating both computational and memory intensities. With the useful code optimization guideline based on such metrics, we demonstrate that MSSG can achieve an excellent peak performance ratio of 32.2% on the Earth Simulator with the single-core performance found to be a key to reduced time-to-solution.

Paper available at ACM.

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Development of software-and-hardware platform for creating digital models of "smart" industrial complexes and manufacturing control system.

Interested parties contact: neurocomputer@yandex.ru

Trends in the development of mining and processing industry indicate, that in the near future mainly "hard"; and remote territories will be developed, and also mineral ore deposits, which have a number of problematic physiographic, climatic and natural conditions, and other important features including remoteness of the territory and adverse natural conditions, complex geological and geophysical conditions, shortage on energy resources, lack of human resources and qualified staff, complex and insufficiently developed transport infrastructure.

To archieve the economic efficincy of the development of such facilities there is a serious need for deep-automated, "deserted" industries with elements of "artificial intelligence" - "smart" industrial complexes, (SIC) based on flexible quasi-module architecture. This requires the creation of computer models of complicated industrial complexes, intelligent control systems of technological, power and transportation manufacturing processes using embedded systems, SCADA, MES technologies and their intergration in the single technological platform applying in CAD/CAE and PLM systems.

Abstract:

Graphics processing units (GPUs) have proven very robust architectures for performing intensive scientific calculations, resulting in speedups as high as several hundred times. In this paper, the GPU acceleration of a radiation code for use in creating simulated satellite observations of predicted climate change scenarios is explored, particularly the prospect of porting an already existing and widely used radiation transport code to a GPU version that fully exploits the parallel nature of GPUs. The porting process is attempted with a simple radiation code, revealing that this process centers on creating many copies of variables and inlining function/subroutine calls. A resulting speedup of about 25x is reached. This is less than the speedup achieved from a radiation code built for CUDA from scratch, but it was achieved with an already existing radiation code using the PGI Accelerator to automatically generate CUDA kernels, and this demonstrates a possible strategy to speed up other existing models like MODTRAN and LBLRTM.

Paper available at IEEE.

Abstract:

WRF-Chem is the WRF coupled with Chemistry. The model simulates the coupling between atmospheric dynamics, radiation and chemistry, and is used for investigation of regional-scale air quality, field program analysis, and cloud-scale interactions between clouds and chemistry. WRF-Chem can predict transport of atmospheric constituents and radiation of O3 and UV [1]. The WRF-Chem processing takes long execution time, and needs high storage space. The porting to Grid Computing and GPU can significantly reduce the overall run-time, since the model supports distributed and shared memory computations. Grid Computing and GPU are two innovative technologies in High Performance Computing, aiming to accelerate compute-intensive applications.

Paper available at IEEE.