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Indian Government Laboratory Selects Infortrend

To power HPC projects in Weather Research and Forecasting

Infortrend Technology, Inc. empowers a government-affiliated research laboratory in India to enhance the speed and accuracy of their HPC projects, specifically the Weather Research and Forecasting (WRF) Model, with EonStor GS enterprise unified storage solution.

Indian Government Laboratory Select Infortrend

The Indian government-affiliated research laboratory is the country’s prime center specializing in fundamental and applied research in atmospheric and space sciences. For weather forecasting and atmospheric research needs, the laboratory leverages the WRF Model running on the on-premises HPC cluster. Recently, the HPC cluster has expanded, and so has the complexity of the WRF Model. This increased requirements for storage, as its insufficient performance slowed down WRF simulations and affected weather forecasting accuracy. Consequently, the laboratory found it necessary to replace the existing out-of-date storage with a new solution.

The research laboratory chose Infortrend’s EonStor GS 4000U hybrid flash NVMe storage. The solution is integrated through 100GbE RDMA and loaded with 24×15.36 TB NVMe SSD, delivering up to 1,100,000 IO/s and 24GB/s read and 12GB /s write throughput. It can handle multiple tasks and computations for complex WRF simulations. To store large amounts of data generated during these processes, it provides a storage capacity of 368.6TB. The deployment of GS 4000U contributed to more accurate weather forecasts and the successful completion of meteorological research projects. Furthermore, when the volume of research data expands and requires higher performance and capacity, GS can be expanded through both scale-out and scale-up.

Infortrend’s storage solution has unlocked new opportunities for our WRF Model: Now its output speed and accuracy have greatly improved. We chose Infortrend because it offers high-performance and high-capacity storage at a competitive price,” said the head of the computing and data management division at the Research Laboratory.

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