3 citations · 3 across the 4 of their papers we have counts for
5 papers
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
Jacob O. Tørring, Carl Hvarfner, Luigi Nardi +1
Bayesian optimization is a powerful method for automating tuning of compilers. The complex landscape of autotuning provides a myriad of rarely considered structural challenges for…
Towards a Benchmarking Suite for Kernel Tuners
Jacob O. Tørring, Ben van Werkhoven, Filip Petrovic +3
As computing system become more complex, it is becoming harder for programmers to keep their codes optimized as the hardware gets updated. Autotuners try to alleviate this by hidin…
Analyzing Search Techniques for Autotuning Image-based GPU Kernels: The Impact of Sample Sizes
Jacob O. Tørring, Anne C. Elster
Modern computing systems are increasingly more complex, with their multicore CPUs and GPUs accelerators changing yearly, if not more often. It thus has become very challenging to w…
LS-CAT: A Large-Scale CUDA AutoTuning Dataset
Lars Bjertnes, Jacob O. Tørring, Anne C. Elster
The effectiveness of Machine Learning (ML) methods depend on access to large suitable datasets. In this article, we present how we build the LS-CAT (Large-Scale CUDA AutoTuning) da…
Autotuning Benchmarking Techniques: A Roofline Model Case Study
Jacob Odgård Tørring, Jan Christian Meyer, Anne C. Elster
Peak performance metrics published by vendors often do not correspond to what can be achieved in practice. It is therefore of great interest to do extensive benchmarking on core ap…