Welcome to PyOpenCL’s documentation!¶

PyOpenCL gives you easy, Pythonic access to the OpenCL parallel computation API. What makes PyOpenCL special?

  • Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code.

  • Completeness. PyOpenCL puts the full power of OpenCL’s API at your disposal, if you wish. Every obscure get_info() query and all CL calls are accessible.

  • Automatic Error Checking. All errors are automatically translated into Python exceptions.

  • Speed. PyOpenCL’s base layer is written in C++, so all the niceties above are virtually free.

  • Helpful Documentation. You’re looking at it. ;)

  • Liberal license. PyOpenCL is open-source under the MIT license and free for commercial, academic, and private use.

Here’s an example, to give you an impression:

#!/usr/bin/env python

import numpy as np

import pyopencl as cl


rng = np.random.default_rng()
a_np = rng.random(50000, dtype=np.float32)
b_np = rng.random(50000, dtype=np.float32)

ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)

mf = cl.mem_flags
a_g = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=a_np)
b_g = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=b_np)

prg = cl.Program(ctx, """
__kernel void sum(
    __global const float *a_g, __global const float *b_g, __global float *res_g)
{
  int gid = get_global_id(0);
  res_g[gid] = a_g[gid] + b_g[gid];
}
""").build()

res_g = cl.Buffer(ctx, mf.WRITE_ONLY, a_np.nbytes)
knl = prg.sum  # Use this Kernel object for repeated calls
knl(queue, a_np.shape, None, a_g, b_g, res_g)

res_np = np.empty_like(a_np)
cl.enqueue_copy(queue, res_np, res_g)

# Check on CPU with Numpy:
error_np = res_np - (a_np + b_np)
print(f"Error:\n{error_np}")
print(f"Norm: {np.linalg.norm(error_np):.16e}")
assert np.allclose(res_np, a_np + b_np)

(You can find this example as examples/demo.py in the PyOpenCL source distribution.)

Tutorials¶

Contents¶

Note that this guide does not explain OpenCL programming and technology. Please refer to the official Khronos OpenCL documentation for that.

PyOpenCL also has its own web site, where you can find updates, new versions, documentation, and support.

Indices and tables¶