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Forum Teratec 2021
Thursday June 24

Workshop 06 - 16:00 to 18:00

New Storage Paradigms to Tackle Exascale Challenges
Chaired by Philippe Deniel, chef du Laboratoire architecture du stockage et des systèmes, CEA DAM

Extreme Data Challenges in Numerical Weather Prediction - Managing Exascale datasets
By Tiago Quintino, Team Leader, ECMWF

Numerical Weather Prediction (NWP) is a highly data intensive HPC application. ECMWF operational weather forecasts generates massive amounts of I/O in short bursts, accumulating to tens of TiB in hourly forecast cycle windows. From this output, millions of user-defined daily products are generated and disseminated to member states and commercial customers all over the world. These products are processed from the raw output of the IFS model, within the time critical path and under strict delivery schedule.

With upcoming programs such as EuroHPC and Destination Earth, in addition to ECMWF's own 2025 NWP strategy, an upcoming rise in resolution and growing popularity will increase both the size and number of these weather forecast products, as we enter the Exascale computing era.

The adoption of software-defined, semantic data storage including object stores for the time-critical operations has opened the door for more comprehensive improvements to the NWP post-processing chain and enabled new access paths to very high-resolution time critical datasets. These improvements will bring product generation and data analytics closer to the NWP model and the model output data, to build true semantic-driven, data-centric processing and analytics workflows, including data-intensive novel Machine Learning models.

These are part of ECMWF plans to achieve Exascale NWP by 2025 and to empower our users and member states with novel and increased usage of our weather forecast data. As Exascale NWP datasets are expected to feature between 250 TiB to 1 PiB per forecast cycle, the data-centric approach and the semantic access to the data is critical to enable their efficient usage, minimise data transport and bring post-processing and insight discovery closer to the data source.

We present the Exascale IO challenges ECMWF is facing, and the latest developments in model I/O, product generation and data access and storage. We show how ECMWF is reworking our operational workflows to adapt to forthcoming new architectures and memory-storage hierarchies, while building the API's that will empower the users to fully utilise rich, dense Exascale datasets.

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