🔥 #AMDlabnotes presents another new article - this time to assist data scientists/ML practitioners get their #PyTorch or #TensorFlow environment up and running on #AMD #GPUs 🔥
Head over to #GPUOpen now to have a read: https://gpuopen.com/learn/amd-lab-notes/amd-lab-notes-pytorch-tensorflow-env-readme/?utm_source=mastodon&utm_medium=social&utm_campaign=amdlabnotes
Need to run large MPI jobs across multiple #AMD GPUs?
Don't miss our latest #AMDlabnotes blog post covering #GPU-aware MPI with #ROCm support 👇
#AMDlabnotes presents two brand new blog posts covering #GPU kernel optimization tips and tricks! 🔥
Firstly, we present a post about understanding and controlling register pressure:
https://gpuopen.com/learn/amd-lab-notes/amd-lab-notes-register-pressure-readme/?utm_source=mastodon&utm_medium=social&utm_campaign=amdlabnotes
And secondly, we present the third part of the Finite Difference Method #Laplacian series.
This blog covers even more optimizations to maximize performance on #AMD GPUs:
https://gpuopen.com/learn/amd-lab-notes/amd-lab-notes-finite-difference-docs-laplacian_part3/?utm_source=mastodon&utm_medium=social&utm_campaign=amdlabnotes
#AMDlabnotes presents a brand-new blog post on the various profiling tools provided by AMD.
It also includes guidance on why a developer might leverage one tool over another.
Check out the link below to find out more!
Ever wonder how #memory is managed on accelerated #HPC systems?
#AMDlabnotes presents an overview for #AMD Instinct™ MI200 #GPUs.
Want to build #ROCm on your #Linux workstation? 🐧
#AMDlabnotes presents a new blog post covering three possible ways to install ROCm.
Take a look now over on on #gpuopen
