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Content provider: Griffith University  or Pawsey Supercomputing Resea... 

AMD Profiling

The AMD profiling workshop covers the AMD suite of tools for development of HPC applications on AMD GPUs.

You will learn how to use the rocprof profiler and trace visualization tool that has long been available as part of the ROCm software suite.

You will also learn how to use the new...

Keywords: supercomputing, performance, GPUs, CPUs, AMD, HPC, ROCm

Resource type: activity

AMD Profiling https://dresa.org.au/materials/amd-profiling The AMD profiling workshop covers the AMD suite of tools for development of HPC applications on AMD GPUs. You will learn how to use the rocprof profiler and trace visualization tool that has long been available as part of the ROCm software suite. You will also learn how to use the new Omnitools - Omnitrace and Omniperf - that were introduced at the end of 2022. Omnitrace is a powerful tracing profiler for both CPU and GPU. It can collect data from a much wider range of sources and includes hardware counters and sampling approaches. Omniperf is a performance analysis tool that can help you pinpoint how your application is performing with a visual view of the memory hierarchy on the GPU as well as reporting the percentage of peak for many different measurements. training@pawsey.org.au supercomputing, performance, GPUs, CPUs, AMD, HPC, ROCm
Evaluate Application Performance using TAU and E4S

In this workshop, you learn about the Extreme-scale Scientific Software Stack and the TAU Performance System® and its interfaces to other tools and libraries. The workshop includes sample codes that illustrate the different instrumentation and measurement choices.

Topics covered include...

Keywords: supercomputing, TAU, E4S, Performance, ROCm, OpenMP

Resource type: activity

Evaluate Application Performance using TAU and E4S https://dresa.org.au/materials/evaluate-application-performance-using-tau-and-e4s In this workshop, you learn about the Extreme-scale Scientific Software Stack and the TAU Performance System® and its interfaces to other tools and libraries. The workshop includes sample codes that illustrate the different instrumentation and measurement choices. Topics covered include generating performance profiles and traces with memory utilization and headroom, I/O, and interfaces to ROCm, including ROCProfiler and ROCTracer with support for collecting hardware performance data. The workshop also covers instrumentation of OpenMP programs using OpenMP Tools Interface (OMPT), including support for target offload and measurement of a program’s memory footprint. During the session, there are hands-on activities on scalable tracing using OTF2 and visualization using the Vampir trace analysis tool. Performance data analysis using ParaProf and PerfExplorer are demonstrated using the performance data management framework (TAUdb) that includes TAU’s performance database. training@pawsey.org.au supercomputing, TAU, E4S, Performance, ROCm, OpenMP
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://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 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://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 supercomputing, C/C++, Programming
Introduction to REDCap at Griffith University

This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases.

Keywords: REDCap, survey instruments

Resource type: tutorial

Introduction to REDCap at Griffith University https://dresa.org.au/materials/introduction-to-redcap-at-griffith-university This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases. y.banens@griffith.edu.au REDCap, survey instruments mbr phd ecr researcher support
Introducing Computational Thinking

This workshop is for researchers at all career stages who want to understand the uses and the building blocks of computational thinking. This skill is useful for all kinds of problem solving, whether in real life or in computing.

The workshop will not teach computer programming per se. Instead...

Keywords: computational skills, data skills

Resource type: tutorial

Introducing Computational Thinking https://dresa.org.au/materials/introducing-computational-thinking This workshop is for researchers at all career stages who want to understand the uses and the building blocks of computational thinking. This skill is useful for all kinds of problem solving, whether in real life or in computing. The workshop will not teach computer programming per se. Instead it will cover the thought processes involved should you want to learn to program. s.stapleton@griffith.edu.au computational skills, data skills
Advanced Data Wrangling with OpenRefine

This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine.

Keywords: data skills, data

Resource type: tutorial

Advanced Data Wrangling with OpenRefine https://dresa.org.au/materials/advanced-data-wrangling-with-openrefine This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine. s.stapleton@griffith.edu.au data skills, data mbr phd ecr researcher support professional
Introduction to Data Cleaning with OpenRefine

Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data...

Keywords: data skills, Data analysis

Resource type: tutorial

Introduction to Data Cleaning with OpenRefine https://dresa.org.au/materials/introduction-to-data-cleaning-with-openrefine Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data in a structured or semi-structured format. s.stapleton@griffith.edu.au; Sharron Stapleton data skills, Data analysis mbr phd ecr researcher support professional
10 Reproducible Research things - Building Business Continuity

The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are...

Keywords: reproducibility, data management

Resource type: tutorial, video

10 Reproducible Research things - Building Business Continuity https://dresa.org.au/materials/9-reproducible-research-things-building-business-continuity The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are replicable due to lack of information on the process. Therefore, reproducibility in research is extremely important. Researchers genuinely want to make their research more reproducible, but sometimes don’t know where to start and often don’t have the available time to investigate or establish methods on how reproducible research can speed up every day work. We aim for the philosophy “Be better than you were yesterday”. Reproducibility is a process, and we highlight there is no expectation to go from beginner to expert in a single workshop. Instead, we offer some steps you can take towards the reproducibility path following our Steps to Reproducible Research self paced program. Video: https://www.youtube.com/watch?v=bANTr9RvnGg Tutorial: https://guereslib.github.io/ten-reproducible-research-things/ a.miotto@griffith.edu.au; s.stapleton@griffith.edu.au; i.jennings@griffith.edu.au; Sharron Stapleton Isaac Jennings reproducibility, data management masters phd ecr researcher support
Data Storytelling

Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert...

Keywords: data storytelling, data visualisation

Data Storytelling https://dresa.org.au/materials/data-storytelling Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert your insights and discovery from data into stories to share with non-experts with a language they understand. But how? This tutorial helps you construct stories that incite an emotional response and create meaning and understanding for the audience by applying data storytelling techniques. m.yamaguchi@griffith.edu.au a.miotto@griffith.edu.au data storytelling, data visualisation support masters phd researcher
Porting the multi-GPU SELF-Fluids code to HIPFort

In this presentation by Dr. Joseph Schoonover of Fluid Numerics LLC, Joe shares their experience with the porting process for SELF-Fluids from multi-GPU CUDA-Fortran to multi-GPU HIPFort.

The presentation covers the design principles and roadmap for SELF and the strategy to port from...

Keywords: AMD, GPUs, supercomputer, supercomputing

Resource type: presentation

Porting the multi-GPU SELF-Fluids code to HIPFort https://dresa.org.au/materials/porting-the-multi-gpu-self-fluids-code-to-hipfort In this presentation by Dr. Joseph Schoonover of Fluid Numerics LLC, Joe shares their experience with the porting process for SELF-Fluids from multi-GPU CUDA-Fortran to multi-GPU HIPFort. The presentation covers the design principles and roadmap for SELF and the strategy to port from Nvidia-only platforms to AMD & Nvidia GPUs. Also discussed are the hurdles encountered along the way and considerations for developing multi-GPU accelerated applications in Fortran. SELF is an object-oriented Fortran library that supports the implementation of Spectral Element Methods for solving partial differential equations. SELF-Fluids is an implementation of SELF that solves the compressible Navier Stokes equations on CPU only and GPU accelerated compute platforms using the Discontinuous Galerkin Spectral Element Method. The SELF API is designed based on the assumption that SEM developers and researchers need to be able to implement derivatives in 1-D and divergence, gradient, and curl in 2-D and 3-D on scalar, vector, and tensor functions using spectral collocation, continuous Galerkin, and discontinuous Galerkin spectral element methods. The presentation discussion is placed in context of the Exascale era, where we're faced with a zoo of available compute hardware. Because of this, SELF routines provide support for GPU acceleration through AMD’s HIP and support for multi-core, multi-node, and multi-GPU platforms with MPI. training@pawsey.org.au AMD, GPUs, supercomputer, supercomputing
Embracing new solutions for in-situ visualisation

This PPT was used by Jean Favre, senior visualisation software engineer at CSCS, the Swiss National Supercomputing Centre during his presentation at P'Con '21 (Pawsey's first PaCER Conference).

This material discusses the upcoming release of ParaView v5.10, a leading scientific visualisation...

Keywords: ParaView, GPUs, supercomputer, supercomputing, visualisation, data visualisation

Resource type: presentation

Embracing new solutions for in-situ visualisation https://dresa.org.au/materials/embracing-new-solutions-for-in-situ-visualisation This PPT was used by Jean Favre, senior visualisation software engineer at CSCS, the Swiss National Supercomputing Centre during his presentation at P'Con '21 (Pawsey's first PaCER Conference). This material discusses the upcoming release of ParaView v5.10, a leading scientific visualisation application. In this release ParaView consolidates its implementation of the Catalyst API, a specification developed for simulations and scientific data producers to analyse and visualise data in situ. The material reviews some of the terminology and issues of different in-situ visualisation scenarios, then reviews early Data Adaptors for tight-coupling of simulations and visualisation solutions. This is followed by an introduction of Conduit, an intuitive model for describing hierarchical scientific data. Both ParaView-Catalyst and Ascent use Conduit’s Mesh Blueprint, a set of conventions to describe computational simulation meshes. Finally, the materials present CSCS’ early experience in adopting ParaView-Catalyst and Ascent via two concrete examples of instrumentation of some proxy numerical applications. training@pawsey.org.au ParaView, GPUs, supercomputer, supercomputing, visualisation, data visualisation
Merit Allocation Training for 2022

This merit allocation training session provides critical information for researchers considering to apply for time on Pawsey’s new Setonix supercomputer in 2022.

Keywords: supercomputer, supercomputing, merit allocation, allocation

Resource type: video

Merit Allocation Training for 2022 https://dresa.org.au/materials/merit-allocation-training-for-2022 This merit allocation training session provides critical information for researchers considering to apply for time on Pawsey’s new Setonix supercomputer in 2022. training@pawsey.org.au supercomputer, supercomputing, merit allocation, allocation