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Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures., , , , and . CoRR, (2021)A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit., , , , , , and . CoRR, (2019)Towards a Benchmarking Suite for Kernel Tuners., , , , , and . IPDPS Workshops, page 724-733. IEEE, (2023)Autotuning of OpenCL Kernels with Global Optimizations., , and . ANDARE@PACT, page 2:1-2:6. ACM, (2017)Kernel Tuning Toolkit., and . SoftwareX, (May 2023)Using hardware performance counters to speed up autotuning convergence on GPUs., , , , and . CoRR, (2021)Using hardware performance counters to speed up autotuning convergence on GPUs., , , , and . J. Parallel Distributed Comput., (2022)A benchmark set of highly-efficient CUDA and OpenCL kernels and its dynamic autotuning with Kernel Tuning Toolkit., , , , , , and . Future Gener. Comput. Syst., (2020)Umpalumpa: a framework for efficient execution of complex image processing workloads on heterogeneous nodes., , , , , and . Computing, 105 (11): 2389-2417 (November 2023)