“CPUs and GPUs are both useful and each has its own place in our
toolbox”
“In the context of GPU programming, we often refer to the GPU as the
device and the CPU as the host”
“Using GPUs to accelerate computation can provide large performance
gains”
“Using the GPU with Python is not particularly difficult”
Using your GPU with CuPyIntroduction to CuPyConvolution in PythonConvolution on the CPU Using SciPyConvolution on the GPU Using CuPyMeasuring performanceValidationA shortcut: performing NumPy routines on the GPUA real world example: image processing for radio astronomySource measurements
“CuPy provides GPU accelerated version of many NumPy and Scipy
functions.”
“Always have CPU and GPU versions of your code so that you can
compare performance, as well as validate your code.”