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Keywords: fish  or reproducibility  or GPUs 

7 Steps towards Reproducible Research

This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.

We will also examine how Reproducible Research builds business continuity...

Keywords: reproducibility, Reproducibility, reproducible workflows

Resource type: full-course, tutorial

7 Steps towards Reproducible Research https://dresa.org.au/materials/7-steps-towards-reproducible-research This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed. We will also examine how Reproducible Research builds business continuity into your research group, how the culture in your institute ecosystem can affect Reproducibility and how you can identify and address risks to your knowledge. The workshop can be used as self-paced or as an instructor Amanda Miotto - a.miotto@griffith.edu.au reproducibility, Reproducibility, reproducible workflows phd support
How can software containers help your research?

This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility. 

Software Containers in research are a solution that addresses the challenge of a...

Keywords: containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material

How can software containers help your research? https://dresa.org.au/materials/how-can-software-containers-help-your-research-ca0f9d41-d83b-463b-a548-402c6c642fbf This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility.  Software Containers in research are a solution that addresses the challenge of a replicable computational environment and supports reproducibility of research results. Understanding the concept of software containers enables researchers to better communicate their research needs with their colleagues and other researchers using and developing containers. Watch the video here: https://www.youtube.com/watch?v=HelrQnm3v4g If you want to share this video please use this: Australian Research Data Commons, 2021. How can software containers help your research?. [video] Available at: https://www.youtube.com/watch?v=HelrQnm3v4g DOI: http://doi.org/10.5281/zenodo.5091260 [Accessed dd Month YYYY]. contact@ardc.edu.au Martinez, Paula Andrea (type: ProjectLeader) Sam Muirhead (type: Producer) The ARDC Communications Team (type: Editor) The ARDC Skills and Workforce Development Team (type: ProjectMember) The ARDC eResearch Infrastructure & Services (type: ProjectMember) The ARDC Nectar Cloud Services team (type: ProjectMember) containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material
CheckEM User Guide

CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for...

Keywords: stereo-video, fish, annotation

CheckEM User Guide https://dresa.org.au/materials/checkem-user-guide CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for common inaccuracies made whilst annotating stereo imagery. CheckEM creates interactive plots and tables in a graphical interface, and provides summarised data and a report of potential errors to download. brooke.gibbons@uwa.edu.au stereo-video, fish, annotation
EventMeasure Annotation Guide

EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length

Keywords: fish, stereo-video, annotation

EventMeasure Annotation Guide https://dresa.org.au/materials/eventmeasure-annotation-guide EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length tim.langlois@uwa.edu.au fish, stereo-video, annotation
Stereo-video workflows for fish and benthic ecologists

Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range...

Keywords: stereo-video, fish, sharks, habitats

Resource type: tutorial

Stereo-video workflows for fish and benthic ecologists https://dresa.org.au/materials/stereo-video-workflows-for-fish-and-benthic-ecologists Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way. tim.langlois@uwa.edu.au stereo-video, fish, sharks, habitats
PCon Preparing applications for El Capitan and beyond

As Lawrence Livermore National Laboratories (LLNL) prepares to stand up its next supercomputer, El Capitan, application teams prepare to pivot to another GPU architecture.

This talk presents how the LLNL application teams made the transition from distributed-memory, CPU-only architectures to...

Keywords: GPUs, supercomputing, HPC, PaCER

PCon Preparing applications for El Capitan and beyond https://dresa.org.au/materials/pcon-preparing-applications-for-el-capitan-and-beyond As Lawrence Livermore National Laboratories (LLNL) prepares to stand up its next supercomputer, El Capitan, application teams prepare to pivot to another GPU architecture. This talk presents how the LLNL application teams made the transition from distributed-memory, CPU-only architectures to GPUs. They share institutional best practices. They discuss new open-source software products as tools for porting and profiling applications and as avenues for collaboration across the computational science community. Join LLNL's Erik Draeger and Jane Herriman, who presented this talk at Pawsey's PaCER Conference in September 2023. training@pawsey.org.au Pawsey Supercomputing Research Centre GPUs, supercomputing, HPC, PaCER masters phd researcher ecr support professional ugrad
OpenCL

Supercomputers make use of accelerators from a variety of different hardware vendors, using devices such as multi-core CPU’s, GPU’s and even FPGA’s. OpenCL is a way for your HPC application to make effective use of heterogeneous computing devices, and to avoid code refactoring for new HPC...

Keywords: supercomputing, Pawsey Supercomputing Centre, CPUs, GPUs, OpenCL, FPGAs

Resource type: activity

OpenCL https://dresa.org.au/materials/opencl Supercomputers make use of accelerators from a variety of different hardware vendors, using devices such as multi-core CPU’s, GPU’s and even FPGA’s. OpenCL is a way for your HPC application to make effective use of heterogeneous computing devices, and to avoid code refactoring for new HPC infrastructure. training@pawsey.org.au Toby Potter supercomputing, Pawsey Supercomputing Centre, CPUs, GPUs, OpenCL, FPGAs masters ecr researcher support
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
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
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
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