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An easy to use CUDA/OpenCL kernel tuner in Python

Project description

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Create optimized GPU applications in any mainstream GPU programming language (CUDA, HIP, OpenCL, OpenACC).

What Kernel Tuner does:


  • First, make sure you have your CUDA, OpenCL, or HIP compiler installed
  • Then type: pip install kernel_tuner[cuda], pip install kernel_tuner[opencl], or pip install kernel_tuner[hip]
  • or why not all of them: pip install kernel_tuner[cuda,opencl,hip]

More information on installation, also for other languages, in the installation guide.


import numpy as np
from kernel_tuner import tune_kernel

kernel_string = """
__global__ void vector_add(float *c, float *a, float *b, int n) {
    int i = blockIdx.x * block_size_x + threadIdx.x;
    if (i<n) {
        c[i] = a[i] + b[i];

n = np.int32(10000000)

a = np.random.randn(n).astype(np.float32)
b = np.random.randn(n).astype(np.float32)
c = np.zeros_like(a)

args = [c, a, b, n]

tune_params = {"block_size_x": [32, 64, 128, 256, 512]}

tune_kernel("vector_add", kernel_string, n, args, tune_params)

More examples here.


Kernel Tuner ecosystem

C++ magic to integrate auto-tuned kernels into C++ applications

C++ data types for mixed-precision CUDA kernel programming

Monitor, analyze, and visualize auto-tuning runs

Communication & Contribution

  • GitHub Issues: Bug reports, install issues, feature requests, work in progress
  • GitHub Discussion group: General questions, Q&A, thoughts

Contributions are welcome! For feature requests, bug reports, or usage problems, please feel free to create an issue. For more extensive contributions, check the contribution guide.


If you use Kernel Tuner in research or research software, please cite the most relevant among the publications on Kernel Tuner. To refer to the project as a whole, please cite:

  author  = {Ben van Werkhoven},
  title   = {Kernel Tuner: A search-optimizing GPU code auto-tuner},
  journal = {Future Generation Computer Systems},
  year = {2019},
  volume  = {90},
  pages = {347-358},
  url = {},
  doi = {}

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