PASC 2019 Minisymposia

Various data-intense scientific domains must deal with exabytes of data before they reach the exaflop. Data management at these extreme scales is challenging and covers not only pre-processing, data production, and data analysis workflows. While there are many research approaches and science databases that aim to manage data and improved their limits over time, practitioners still struggle to manage their data in the petabyte era. For instance, achieving high performance and providing means to easily localize data upon request. With billions of files, the scalability of the manual and fine-grained data management in HPC environments reaches its limitations. Various domain-specific solutions have been developed that mitigate performance and management issues enabling data management in the petabyte era. However, due to new storage technologies and heterogeneous environments, the challenges increase and so does the development effort for individual solutions. In this minisymposium, speakers from environmental science (Met Office and ECMWF), CERN, and the Square Kilometre Array will address this matter for different domains; each speaker will present the challenges faced in their scientific domain today, give an outlook for the future, and present state-of-the-art approaches the community follows to mitigate the data deluge.

See https://pasc19.pasc-conference.org/program/schedule

For decades, weather and climate models have significantly improved in predictive skill. This was possible, among other things, due to a steadily increasing resolution that became accessible through increasing supercomputing capacity. Increases in resolution from 500 km to 5 km have been enabled by a million-fold increase in computational power. Global kilometre-resolving simulations will eventually allow to represent individual clouds and deep convection explicitly within simulations, which is promising an additional jump in predictive skill. However, it is still not clear if and when these simulations will become reality, despite the upcoming exascale era. In this minisymposium, recent advances towards global kilometre-resolving weather and climate simulation are discussed. This will include an assessment of I/O and in-situ approaches to cope with related big data challenges, algorithmic and performance enhancements for the models, and discussions on the scientific value of these high-resolution simulations. Amongst others, findings from the HPC-driven European centre of excellence ESiWACE on exascale computing for weather and climate models as well as from the international DYAMOND intercomparison initiative will be presented to complement the HPC and science picture and to stimulate discussions about the grand challenge to allow operational weather and climate simulation at a resolution of O(1km).

This minisymposium features talks by Philipp Neumann, Peter Bauer, Kim Serradell (all ESiWACE) and Masaki Satoh (DYAMOND).

Minisymposium: "Interoperability of Abstractions, High Level Languages and Intermediate Representations for High Productivity of Weather and Climate Models", C. Osuna (MeteoSwiss), Willem Deconinck (ECMWF), Rupert Ford (STFC)

Numerical weather prediction and climate models are complex scientific applications that need to run on large parallel computer systems. The rapid change of computing architectures and the increasing diversity of architectures and programming models required to run these applications presents a significant challenge for the modelling community to retain single source codes that run efficiently on multiple architectures, now and in the future. In order to address the performance portability problem, numerous solutions have emerged in recent years: i.e. source-to-source translators, domain specific languages (DSLs) and libraries that abstract details of the efficient implementation of the physical equations. However, each of these solutions applies to a particular domain, and supports certain types of horizontal grids, numerical methods or computational pattern. Reuse of abstractions and tools, such as optimizers, for the weather and climate domain, will be key to enable the sustainability and maintainability of the ecosystem of tools and libraries for weather and climate prediction applications. The standardization of interfaces will allow higher level abstractions to be built which will, in turn, increase scientific productivity by improving the ability to develop models. We will present and discuss recent efforts that have begun on the interoperability and standardization of these abstractions.