Teaching and Learning Stories

Since October 2021, Intersect Australia and the National Computational Infrastructure (NCI) have collaborated to deliver a comprehensive training program, which aims to upskill NCI HPC users on cutting edge digital technologies and tools, including Python, R, and Julia programming; machine learning; research computing; and parallel programming. To date, this program has trained over 600 researchers in 27 courses across 40+ institutions and organisations across Australia. 

In order to better understand how the NCI/Intersect training program has supported the research and professional career of the participants, we arranged to meet with several of the attendees to capture their feedback. This would demonstrate and elucidate how the training program is helping researchers and professionals to more effectively and efficiently utilise cutting edge tools and technologies, as well as NCI’s infrastructure, for their research. 

Our first meeting was with two researchers from the Australian Nuclear Science and Technology Organisation (ANSTO).  Dr Paul Callaghan  is an Imaging Neurophysiologist, who applies PET/CT and SPECT/CT multimodal molecular imaging techniques for investigating animal models of neurological and psychiatric disease. Mr Nicholas Howell is a biologist also working within the Nuclear Science & Technology group. 

When asked about the main reason for attending this training program, Paul told us that “completely inappropriate tools have been and are being used to do the job because of limitations in knowledge. We needed to upskill so we can actually even do a small scale deployment.” Nicholas added that he attended the course so he could effectively work on the same problem with the colleagues at ANSTO.  

“We need to train ourselves in which tools are appropriate for each of the tasks, for example, scripted image processing workflows (using Python/ImageJ), pre processing of data from analytical instruments (for example radiation counters, microplate readers, Python or R), and data visualisation and statistics in R/Python (in particular, using existing code for tests not available in ‘easy’ commercial statistical packages using R).” - Dr Paul Callaghan & Nicholas Howell

Both have attended five different workshops under this training program, so we were interested to know what kept them coming back for more. Nicholas has done both free and paid online courses, which were quite good, but he mentioned that “ the NCI/Intersect courses are really relevant to what I am trying to do. I really enjoyed the training format with live questions and found that difficult concepts have been stepped through very nicely in the courses. I've been getting a lot out of them, so that's why I keep coming back.”. 

Paul has also attended other online courses and found these courses often switched between concepts without explaining why, leaving attendees confused. “You are coding. You're not programming at our stage of the career and many of the other courses are programming courses”, Paul emphasised. Paul also said about the NCI/Intersect courses that “I was able to achieve some tasks using that course material and then build upon it with the next one afterwards.” 

Paul and Nicholas both agreed that the toolset that's being taught in NCI/Intersect courses is entirely valid and well-focused for the deployment and development of their models, which is very different from many of the other online courses.

“The breadth of the NCI/Intersect courses in first the principles of the tools, then the use of that tool for data wrangling, and subsequently visualisation fits very well with our needs. Firstly, we have seen where we need to be, and the NCI/Intersect courses are a way to get there. Both myself and Nick have also done other courses (datacamp, EdX etc), and the focus of the NCI/Intersect courses has led to us being able to leave the training, and able to ‘do’ immediately, as the trainers really understand the differing needs compared to a more generic EdX course.” - Dr Paul Callaghan & Nick Howell

Speaking about the benefits of our hands-on, instructor-led workshops on attendees’ research careers, Nicholas recognised that attendees can be taught, but they don't truly learn until they have an opportunity to practice with the application. In response to what would be missing if they did not have access to these courses, Paul was concerned about the new starters (HDR students, researchers, and scientific staff), who are not trained and are not from a computational background. He said “I think we're doing those students a disservice to force them into using inappropriate tools and we're not going to be competitive without access to the training of the next generation, and it just reinforces the problem as people get busy”. Paul also suggested that it would be helpful, at the university level, to introduce basic concepts of data handling and data management.

This interview and article are jointly prepared by NCI and Intersect.

Fred joined NCI in October last year when he was writing his PhD thesis.

"I'm grateful to undertake this role. Working for a supercomputer facility like NCI was always sitting at the back of my mind. It's where my training naturally grows into."

Majoring in Mathematics through undergraduate study at ANU and following his interest in computational mathematics in his PhD, Fred specialises in fault-tolerant HPC applications.

"While the computation power grows every year, it comes with ever greater energy demands. Solving a petascale matrix problem in an inefficient way can cost as much energy as is used by all the households in Canberra. Ideally, from both the user and the facility's perspective, we want to have fault recovery mechanisms in case of fault occurrences during program execution."

Fred is currently developing the NCI HPC Toolkit for NCI users, a training module that contains a series of parallel APIs and programming models, including OpenMP, MPI and CUDA.

"When I was working on my PhD, my supervisor Associate Professor Linda Stal's program, a 300k C++ parallel code written back in the 90s and used to run on the then supercomputer Fujitsu AP1000, I was amazed that it still compiled and ran smoothly on Gadi, our latest machine, owing to its portable and sustainable implementation. Likewise, my passion is to help our users devise efficient codes that hopefully will run in the future."