Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs

Taabish Jeshani
The University of Western Ontario
The University of Western Ontario, 2023


   title={Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs},

   author={Jeshani, Taabish},



In this thesis, we present KLARAPTOR (Kernel LAunch parameters RAtional Program estimaTOR), a freely available tool to dynamically determine the values of kernel launch parameters of a CUDA kernel. We describe a technique for building a helper program, at the compile-time of a CUDA program, that is used at run-time to determine near-optimal kernel launch parameters for the kernels of that CUDA program. This technique leverages the MWP-CWP performance prediction model, runtime data parameters, and runtime hardware parameters to dynamically determine the launch parameters for each kernel invocation. This technique is implemented within the KLARAPTOR tool, utilizing the LLVM Pass Framework and NVIDIA Nsight Compute CLI profiler. We demonstrate the effectiveness of our approach through experimentation on the PolyBench benchmark suite of CUDA kernels.
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