Infrastructure and Techniques to Accelerate Operational Weather Codes on Next-generation Supercomputers

Temporary Supervisor

Associate Professor Peter Strazdins


Climate and weather models currently consume vast amounts of supercomputer time, with the most dominant component being the atmosphere. In order to make accurate long-range forecasts, BoM requires high resolution global atmosphere and ocean models. Similarly, with the ACCESS project performing large-scale climate simulations, the amount of usage is exploding. However, these models are complex software systems, with large amounts of legacy code. The primary consideration is to correctly encode the science for meaningful simulations; the secondary is performance, particularly on large-scale parallel computers.  State-of-the-art supercomputers are becoming increasingly complex,  with nodes not only being made of highly multiple traditional processing cores, but with multiple manycore accelerators.

The aim of the research would be to investigate techniques to support the efficient porting of key codes used in weather forecasting to supercomputers with heterogeneous nodes, that is multicore main processors augmented with accelerators such as NVIDIA's General Purpose Graphics Processing Units (GP-GPUs).



The goals of this project include (1) analyzing and developing an understanding of the performance and scaling behavior of a selection of operational weather codes, (2) exploring and evaluating new opportunities and techniques for parallelization. This includes the use of new programming paradigms, code transformation tools,  and the use of accelerators such as GPUs and the Xeon Phi. Work on supporting infrastructure includes automated methods to reverse-engineer test harnesses (correctness and performance) for selected performance-critical subroutines and generate kernels for them, methods to automatically refactor the codes for the desired target node architecture, and tools to reliably predict the performance of these codes on future accelerator designs. This infrastructure and techniques can be used to benefit many applications areas, but the project will aim to prove them on selected operational codes of interest to the Bureau of Meteorology, NCI and NVIDIA.


(PhD Level) An Honours degree in computer or computational science or equivalent. Some background in high performance computing  is desirable. Experience in code transformations tools would be ideal. This is a computer science project, knowledge in weather and earth sciences is not required.


Weather science is of increasing importance, and the with it the need to perform efficient and meaningful simulations, especially for medium-term forecasts. This project represents an opportunity to join and make a significant contribution with an international team working in computer and earth sciences. The core of the team will be at ANU and will comprise of up to 3 PhD students. External collaborating organizations potentially include  NVIDIA,  the Bureau of Meteorology, CSIRO, NCI,  NCAR (USA), STFC (UK), RIKEN (Japan), and Sandia National Laboratories. There will be travel and internship oportunities.

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing