Bohrium provides automatic acceleration of array operations in Python/NumPy, C, and C++ targeting multi-core CPUs and GP-GPUs. Forget handcrafting CUDA/OpenCL to utilize your GPU and forget threading, mutexes and locks to utilize your multi-core CPU, just use Bohrium!


  Architecture Support Frontends
  Multi-Core CPU Many-Core GPU Python2/NumPy Python3/NumPy C C++
Mac OS  
  • Lazy Evaluation, Bohrium will lazy evaluate all Python/NumPy operations until it encounters a “Python Read” such a printing an array or having a if-statement testing the value of an array.
  • Views Bohrium supports NumPy views fully thus operating on array slices does not involve data copying.
  • Loop Fusion, Bohrium uses a fusion algorithm that fuses (or merges) array operations into the same computation kernel that are then JIT-compiled and executed. However, Bohrium can only fuse operations that have some common sized dimension and no horizontal data conflicts.
  • Lazy CPU/GPU Communication, Bohrium only moves data between the host and the GPU when the data is accessed directly by Python or a Python C-extension.
  • python -m bohrium, automatically makes import numpy use Bohrium.
  • Jupyter Support, you can use the magic command %%bohrium to automatically use Bohrium as NumPy.
  • Zero-copy interoperability with:
Please note: