Kernel Tuning Toolkit

Authors

PETROVIČ Filip FILIPOVIČ Jiří

Year of publication 2023
Type Article in Periodical
Magazine / Source SoftwareX
MU Faculty or unit

Institute of Computer Science

Citation
Web https://www.sciencedirect.com/science/article/pii/S235271102300081X
Doi http://dx.doi.org/10.1016/j.softx.2023.101385
Keywords Autotuning; GPU optimization; CUDA; OpenCL; Vulkan
Description 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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