  To concisely and effectively demonstrate the capabilities of our program
transformation system Loo.py, we examine a transformation path from two
real-world Fortran subroutines as found in a weather model to a single
high-performance computational kernel suitable for execution on modern GPU
hardware. Along the transformation path, we encounter kernel fusion,
vectorization, prefetch- ing, parallelization, and algorithmic changes achieved
by mechanized conversion between imperative and functional/substitution- based
code, among a number more. We conclude with performance results that
demonstrate the effects and support the effectiveness of the applied
transformations.
