Last week we released version 1.1 of Kernel Tuner, out Python tool for performance, and energy-efficiency, tuning of GPU applications.
https://github.com/KernelTuner/kernel_tuner/releases/tag/1.1.0
Last week we released version 1.1 of Kernel Tuner, out Python tool for performance, and energy-efficiency, tuning of GPU applications.
https://github.com/KernelTuner/kernel_tuner/releases/tag/1.1.0
The university of Leiden published a news item about the imminent release of version 1.0 of Kernel Tuner.
If you are interested in the slides of our SC23 tutorial on "Energy-efficient GPU computing" you can download them at the following link! You can also run the hands-on exercises on Google Colab for free if you want :)
https://github.com/KernelTuner/kernel_tuner_tutorial/blob/master/slides/2023_Supercomputing/SC23.pdf
We are at the United Kingdom Research Software Engineer (#RSEs) Conference (#RSECon23) today hosting 2 sessions:
👉 Our RSE Alessio and PhD Candidates Floris-Jan and Stijn are teaching RSEs how to improve the performance of their #GPU applications using #KernelTuner
👉Our Training Programme Lead, Mateusz, is providing an update on RSE activities @eScienceCenter & in the NL!
My colleagues presented an interesting paper on autotuning GPUs for energy efficiency titled "Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning".
Preprint is already available https://arxiv.org/abs/2211.07260