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Kernel Tuning Toolkit

Filip Petrovič, Jiří Filipovič
Masaryk University, Brno, Czech Republic
SoftwareX, Volume 22, 101385, 2023

@article{petrovivc2023kernel,

   title={Kernel Tuning Toolkit},

   author={Petrovi{v{c}}, Filip and Filipovi{v{c}}, Ji{v{r}}{‘i}},

   journal={SoftwareX},

   volume={22},

   pages={101385},

   year={2023},

   publisher={Elsevier}

}

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Kernel Tuning Toolkit (KTT) is an autotuning framework for CUDA, OpenCL and Vulkan kernels. KTT provides advanced autotuning features such as support for both dynamic (online) and offline tuning, and an ability to tune multiple kernels together with shared tuning parameters. Furthermore, it offers customization features that make integration into larger software suites possible. The framework handles all major steps required for autotuning implementation, including configuration space creation and exploration, kernel code execution and output validation. The public API is available natively in C++ and via bindings in Python.
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