GPU Reduction

Writing a reduction algorithm for CUDA GPU can be tricky. Numba provides a @reduce decorator for converting a simple binary operation into a reduction kernel. An example follows::

import numpy
from numba import cuda

@cuda.reduce
def sum_reduce(a, b):
    return a + b

A = (numpy.arange(1234, dtype=numpy.float64)) + 1
expect = A.sum()      # NumPy sum reduction
got = sum_reduce(A)   # cuda sum reduction
assert expect == got

Lambda functions can also be used here::

sum_reduce = cuda.reduce(lambda a, b: a + b)

The Reduce class

The reduce decorator creates an instance of the Reduce class. Currently, reduce is an alias to Reduce, but this behavior is not guaranteed.

.. autoclass:: numba.cuda.Reduce :members: init, call :member-order: bysource