Skip to content

Version 0.4.4
Compare
Choose a tag to compare
@benvanwerkhoven benvanwerkhoven released this 09 Mar 11:21
· 611 commits to master since this release
0.4.4
d0dc834

Version 0.4.4

Version 0.4.4 adds extended support for energy efficiency tuning. In particular, with the new capability to fit a performance model to the target GPUs power-frequency curve. How to use these features is demonstrated in:
https://github.com/KernelTuner/kernel_tuner/blob/master/examples/cuda/going_green_performance_model.py

And described in the paper:

Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning
R. Schoonhoven, B. Veenboer, B. van Werkhoven, K. J. Batenburg
International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS) at Supercomputing (SC22) 2022
https://arxiv.org/abs/2211.07260

Other than that, we've implemented a new output and metadata JSON format that adheres to the 'T4' auto-tuning schema created by the auto-tuning community at the Lorentz Center workshop in March 2022.

From the changelog:

[0.4.4] - 2023-03-09

Added

  • Support for using time_limit in simulation mode
  • Helper functions for energy tuning
  • Example to show ridge frequency and power-frequency model
  • Functions to store tuning output and metadata

Changed

  • Changed what timings are stored in cache files
  • No longer inserting partial loop unrolling factor of 0 in CUDA
Assets 2
Loading