The CSIRO Conference on Computational and Data Intensive Science

Cloud computing for science

Workshop summary

“Cloud computing is primarily a business phenomenon, not a technological one. The drivers for market uptake are flexibility and cost-efficiency, not technology, which is just an enabler. All of the relevant technologies have long existed. All of the issues associated now with cloud computing have long existed – security, data sovereignty, availability (2.1), service level management, interoperability (2.25), license management, etc. What is different now is that the business imperative is forcing the industry to come up with better solutions for these long-existing problems” (ISO/IEC 17788:2014, Par 2.7 Note).

Cloud computing is changing the way that businesses work. It is also changing the way that science is carried out, and is enabling new science outcomes. This workshop introduces the work that CSIRO is carrying out to support scientists in their adoption and use of the cloud through the introduction of new tools and services that interact with the major Cloud Service Providers. Following up from this, we have three dedicated, hands-on sessions: one by the Pawsey Supercomputing Centre, through their NIMBUS cloud service, followed by two of the major commercial Cloud Service Providers – Amazon Web Services and Google – who will introduce, demonstrate and discuss in an interactive forum the major features of their respective services.


Time Session
09:15 – 09:30 Introduction to the workshop

John Zic, CSIRO

09:30 – 10:30 Overview of CSIRO’s work in cloud computing to enable research and science outcomes

Lead: Brendan Speet, CSIRO

10:30 – 11:00 Morning tea
11:00 – 12:00 Technical introduction to NIMBUS, Pawsey Supercomputing Centre’s Cloud Service for Science

Lead: Mark Gray, Pawsey Supercomputing Centre

12:00 – 13:30 Working Lunch break

NIMBUS workshop continues.

13:30 – 15:00 Workshop session from AWS

Data analytics and Deep Learning on AWS with Jupyter and MXNet

Lead:  Adrian White, AWS

This workshop will take attendees through the basics of AWS and why investigators are using AWS to accelerate their research. Attendees will get hands-on experience creating their own Jupyter Notebook environment on AWS, and then use that environment to explore deep learning approaches on AWS using the MXNet Deep Learning Framework.

By the end of the workshop attendees will have:

  • An introduction to AWS and core services
  • A deeper dive into general compute, GPU and FPGA capabilities on AWS
  • Experience with Jupyter Notebooks and understand why researchers are using them on AWS
  • An introduction to Deep Learning basics
  • Experience training and evaluating deep learning models interactively using MXNet with Jupyter Notebooks using GPUs in the AWS cloud.
15:00 – 15:30 afternoon tea
15:30 – 17:00 Workshop session from Google

Cloud Quest: Scientific Data

Lead: Lak Lakshmanan, Google

Based on the following lab:

Lab Units 4, 5, and 6 will be used to cover the areas of

  • data processing pipelines
  • data exploration,
  • machine learning

The workshop is grounded in practical use cases:

Unit 4 – Distributed Computation of NDVI from Landsat Images using Cloud Dataflow

Unit 5 – Analyzing Natality Data using Datalab and BigQuery

Unit 6 – Predicting baby weight with TensorFlow on Cloud ML Engine

17:00 – 17:15 Wrap-up and close

Date and time

Thursday 20th July, 2017.


Room: Clarendon D, level 2.
Melbourne Convention and Exhibition Centre
1 Convention Place, Melbourne, Victoria

Contact information

John Zic:

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The C3DIS 2017 will bring together researchers with computational and data science specialists from CSIRO, publicly funded research organisations and other invited institutions and organisations. This will enable attendees to share their science outcomes and learnings, and build a community of practice around Computational and Data Intensive science.

Free for CSIRO staff and invited participants