Tag: #parallel computing

The Pawsey Supercomputing Centre are a Tier-1 facility in Australia which enables amazing, ground-breaking science across the nation. Due to this high profile, we have collected Pawsey coverage across a range of national and international media publications.
11 December 2023

GPU to GPU Communication with MPI and Other Topics

GPUs are powerful devices, but one of their main weaknesses is the data transfer to and from the host device. A new feature appeared recently: GPU-to-GPU communications, allowing to bypass the need to send the data back through the host, with appropriate hardware support. This workshop will cover how this can be achieved in MPI

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11 December 2023

Introduction to MPI

Are you interested in distributed memory programming? Are you ready to go beyond using a single node? Any given node has limited resources, whether memory or compute. Being able to scale beyond a single node enables you to leverage more resources, and make use of distributed memory architectures, such as supercomputers.  You can join in-person

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8 December 2023

Using OpenMP with GPUs

GPUs are powerful devices, but not trivial to use. If you want to discover how to offload the execution of your code to GPUs, and leverage the parallelism available on GPUs, then this hands-on workshop is for you. You can join in-person OR virtually. This is a free workshop. Please register only if you plan to

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8 December 2023

Introduction to OpenMP for CPUs

Having multiple cores available only speeds your code when you know how to use them. If you want to discover how to enable CPU parallelism in your code, and have a familiarity with C, C++ or Fortran, then this hands-on workshop is for you.  You can join in-person OR virtually. This is a free workshop.

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7 September 2022

Pawsey, NCI, and NeSI OpenACC GPU Bootcamp

Join Pawsey, NCI, and NeSI as they co-host a 3-day digital GPU Bootcamp. GPU Bootcamps are exciting and unique ways for scientists and researchers to learn how to accelerate codes on GPUs. This virtual event combines virtual “live” sessions with outside work. You will learn intermediate to advanced CUDA optimization techniques for code acceleration. The

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