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!
|Multi-Core CPU||Many-Core GPU||Python2/NumPy||Python3/NumPy||C||C++|
- 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 numpyuse Bohrium.
- Jupyter Support, you can use the magic command
%%bohriumto automatically use Bohrium as NumPy.
- Please note:
- Bohrium is a 64-bit project exclusively.
- Source code is available here: https://github.com/bh107/bohrium
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