HIP Workshop
The Heterogeneous Interface for Portability (HIP) provides a programming framework for harnessing the compute capabilities of multicore processors, such as the MI250X GPU’s on Setonix.
In this course we focus on the essentials of developing HIP applications with a focus on...
Keywords: HIP, supercomputing, Programming, GPUs, MPI, debugging
Resource type: full-course
HIP Workshop
https://support.pawsey.org.au/documentation/display/US/Pawsey+Training+Resources
https://dresa.org.au/materials/hip-workshop
The Heterogeneous Interface for Portability (HIP) provides a programming framework for harnessing the compute capabilities of multicore processors, such as the MI250X GPU’s on Setonix.
In this course we focus on the essentials of developing HIP applications with a focus on supercomputing.
Agenda
- Introduction to HIP and high level features
- How to build and run applications on Setonix with HIP and MPI
- A complete line-by-line walkthrough of a HIP-enabled application
- Tools and techniques for debugging and measuring the performance of HIP applications
training@pawsey.org.au
Pelagos
Pawsey Supercomputing Research Centre
HIP, supercomputing, Programming, GPUs, MPI, debugging
C/C++ Refresher
The C++ programming language and its C subset is used extensively in research environments. In particular it is the language utilised in the parallel programming frameworks CUDA, HIP, and OpenCL.
This workshop is designed to equip participants with “Survival C++”, an understanding of the basic...
Keywords: supercomputing, C/C++, Programming
Resource type: activity
C/C++ Refresher
https://www.youtube.com/playlist?list=PLmu61dgAX-aYsRsejVfwHVhpPU2381Njg
https://dresa.org.au/materials/c-c-refresher
The C++ programming language and its C subset is used extensively in research environments. In particular it is the language utilised in the parallel programming frameworks CUDA, HIP, and OpenCL.
This workshop is designed to equip participants with “Survival C++”, an understanding of the basic syntax, how information is encoded in binary format, and how to compile and debug C++ software.
training@pawsey.org.au
Pelagos
Pawsey Supercomputing Research Centre
supercomputing, C/C++, Programming
WEBINAR: AlphaFold: what's in it for me?
This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023.
Event description
AlphaFold has taken the scientific world by storm with the ability to accurately predict the...
Keywords: Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning
WEBINAR: AlphaFold: what's in it for me?
https://zenodo.org/record/7865494
https://dresa.org.au/materials/webinar-alphafold-what-s-in-it-for-me
This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023.
Event description
AlphaFold has taken the scientific world by storm with the ability to accurately predict the structure of any protein in minutes using artificial intelligence (AI). From drug discovery to enzymes that degrade plastics, this promises to speed up and fundamentally change the way that protein structures are used in biological research.
Beyond the hype, what does this mean for structural biology as a field (and as a career)?
Dr Craig Morton, Drug Discovery Lead at the CSIRO, is an early adopter of AlphaFold and has decades of expertise in protein structure / function, protein modelling, protein – ligand interactions and computational small molecule drug discovery, with particular interest in anti-infective agents for the treatment of bacterial and viral diseases.
Craig joins this webinar to share his perspective on the implications of AlphaFold for science and structural biology. He will give an overview of how AlphaFold works, ways to access AlphaFold, and some examples of how it can be used for protein structure/function analysis.
Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.
Files and materials included in this record:
Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.
Materials shared elsewhere:
A recording of this webinar is available on the Australian BioCommons YouTube Channel:
https://youtu.be/4ytn2_AiH8s
Melissa Burke (melissa@biocommons.org.au)
Morton, Craig (orcid: 0000-0001-5452-5193)
Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning
Learn to Program: Python
Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.
We teach using Jupyter notebooks, which allow program code, results,...
Keywords: Programming, Python
Learn to Program: Python
https://intersect.org.au/training/course/python101
https://dresa.org.au/materials/learn-to-program-python
Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.
We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research.
Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.
#### You'll learn:
- Introduction to the JupyterLab interface for programming
- Basic syntax and data types in Python
- How to load external data into Python
- Creating functions (FUNCTIONS)
- Repeating actions and analysing multiple data sets (LOOPS)
- Making choices (IF STATEMENTS - CONDITIONALS)
- Ways to visualise data in Python
#### Prerequisites:
No prior experience with programming is needed to attend this course.
We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/).
**For more information, please click [here](https://intersect.org.au/training/course/python101).**
training@intersect.org.au
Programming, Python
Accelerating skills development in Data science and AI at scale
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...
Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Accelerating skills development in Data science and AI at scale
https://zenodo.org/record/4287746
https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally.
The talk will also cover our approach as outlined below
• Combined survey of gaps in skills and trainings for Data science and AI
• Provide seats to partners
• Share associate instructors/helpers/volunteers
• Develop combined training materials
• Publish a repository of open source trainings
• Train the trainer activities
• Establish a network of volunteers to deliver trainings at their local regions
Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community.
Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together.
contact@ardc.edu.au
Tang, Titus
AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Monash University - University of Queensland training partnership in Data science and AI
We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...
Keywords: data skills, training partnerships, data science, AI, training material
Monash University - University of Queensland training partnership in Data science and AI
https://zenodo.org/record/4287864
https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai
We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers.
contact@ardc.edu.au
Tang, Titus
data skills, training partnerships, data science, AI, training material
Training resources for sharing and reuse
This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis...
Keywords: FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance
Training resources for sharing and reuse
https://zenodo.org/record/5711887
https://dresa.org.au/materials/training-resources-for-sharing-and-reuse
This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis on sharing and reuse. This was a very collaborative project with the opportunity to work with different target audiences, topics and support expertise. To accommodate for a short timeline. We defined the scope to six topics. 1) Containers in Research 2) Data Governance 3) Software citation and Licensing 4) FAIR Data 101 5) Metadata for Training Materials 6) Machine Learning Resources.
You can watch the video on YouTube here: https://youtu.be/10Yv_BFa-mw
contact@ardc.edu.au
Martinez, Paula Andrea (orcid: 0000-0002-8990-1985)
FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance
Software publishing, licensing, and citation
A short presentation for reuse includes speaker notes.
Making software citable using a code repository, an ORCID and a licence.
Cite as
Liffers, Matthias. (2021, July 12). Software publishing, licensing, and citation. Zenodo. https://doi.org/10.5281/zenodo.5091717
Keywords: software citation, software publishing, software registry, software repository, research software
Resource type: presentation
Software publishing, licensing, and citation
https://zenodo.org/record/5091717#.YQyPtY4zaUk
https://dresa.org.au/materials/software-publishing-licensing-and-citation
A short presentation for reuse includes speaker notes.
Making software citable using a code repository, an ORCID and a licence.
**Cite as**
Liffers, Matthias. (2021, July 12). Software publishing, licensing, and citation. Zenodo. https://doi.org/10.5281/zenodo.5091717
ARDC Contact us: https://ardc.edu.au/contact-us/
Matthias Liffers
software citation, software publishing, software registry, software repository, research software
phd
ecr
researcher
support
ARDC Guide to making Software Citable
A short guide to making software citable using a code repository, an ORCID and a licence.
Cite as
Liffers, Matthias, & Honeyman, Tom. (2021). ARDC Guide to making software citable. Zenodo. https://doi.org/10.5281/zenodo.5003989
Keywords: software citation, software publishing, software registry, software repository, research software
Resource type: guide
ARDC Guide to making Software Citable
https://zenodo.org/record/5003989#.YQyRI44zaUk
https://dresa.org.au/materials/ardc-guide-to-making-software-citable
A short guide to making software citable using a code repository, an ORCID and a licence.
**Cite as**
Liffers, Matthias, & Honeyman, Tom. (2021). ARDC Guide to making software citable. Zenodo. https://doi.org/10.5281/zenodo.5003989
ARDC Contact us: https://ardc.edu.au/contact-us/
Matthias Liffers
Tom Honeyman
software citation, software publishing, software registry, software repository, research software
phd
ecr
researcher
support