Increasing scientific productivity through scalable computation and data

Dr Ben Evans1

1NCI Australia, Canberra, Australia


Since 2008, through a series of collaborative NCRIS programs, a number of significant scientific research activities at NCI that involve scalable computing, data analysis and a large collection of FAIR reference datasets. In particular, these have computing capability to enable significant improvements to the outcomes of climate, weather, geophysics and environmental science, and have become a central infrastructure that is used by the climate community, many NCRIS capabilities (e.g, IMOS, TERN, AuScope, AAL) and government programs (e.g., weather prediction, Digital Earth Australia). The success has meant increased productivity of scientific outcomes and impact for national priorities that have been enabled by these investments.

However, the high performance computing sector has been known for some time that performance is no longer advancing according to Moore’s law and the future of scalable computing will need to evolve in new ways. This required us to reexamine our software and algorithms, increase our effort for improvements and scalability and reconsider some old assumptions of data precision and reproducibility.

The current success of colocating of scientific datasets with HPC computational infrastructure did not happen overnight: they required a long and steady timeline requiring deepening alignment of data and compute to demonstrate the success of the approach.  At the same time, standards for interoperability and interconnectivity between scientific fields have been slowly maturing, and in many cases transdisciplinary science is now a reality.

In this talk I will discuss the journey so far and challenges ahead.


Dr Ben Evans is NCI’s Associate Director for Research Engagements and Initiatives and is responsible for driving innovation and development of future capabilities for HPC and data-driven science with NCI major stakeholders, including NCI’s partners, research communities, and national and international collaborators. He leads a team of specialists in data science and data management, computational model and software development, and scientific visualisations, with the focus on harnessing the full power of NCI’s National Tier 1 high-performance capabilities, digital assets, and new innovations to address the ongoing challenges of high-performance computing and data-driven research.

Ben has developed NCI’s strategic programs in Climate, Weather, Environment, and Geoscience, which support research and national/international collaborations across the university and government scientific community. The goal has been to develop the computational and data-intensive science expertise to improve the performance of high-resolution models and provide sustainable research platforms which support both the novice user as well as more advanced science and innovative data analysis techniques.


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