Version 1.4.0

This release marks a large step for Kernel Tuner in terms of new functionality and changes. The most important additions/changes being:

• Parallel tuning on multiple GPUs and GPU clusters using Ray
• Multi-objective optimization through Pymoo
• Change of default CUDA backend from PyCuda to cuda-python

And of course many other smaller additions and fixes. Below is a more detailed overview of all merged pull requests:

What's Changed

• Add AMDSMIObserver that uses amdsmi to measure energy by @stijnh in #372
• Added the best generated LLaMEA algorithms by @fjwillemsen in #368
• Add support for template kernels in the NVCUDA backend by @stijnh in #367
• Add support for template kernels in HIP by @stijnh in #366
• Programmatic imports by @benvanwerkhoven in #359
• Add parallel tuning on multiple remote GPUs using Ray by @isazi in #328
• Multiobjective optimization by @maric-a-b in #358
• update citation info by @benvanwerkhoven in #382
• Fix how UUID/PCI bus is acquired in CUDA backends and processed by NVML by @stijnh in #383
• add support for setting sm count in nvcuda backend by @benvanwerkhoven in #384
• update changelog by @benvanwerkhoven in #387
• Add AMDSMIContinuousObserver by @stijnh in #386
• fix for using locked clocks by @benvanwerkhoven in #390
• Default cuda backend selection by @benvanwerkhoven in #385
• fix issue with nvml cleanup in case of crash, issue #377 by @benvanwerkhoven in #392

New Contributors

• @maric-a-b made their first contribution in #358

Full Changelog: 1.3.3...1.4.0