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Add tests of CUDA caching based on CPU caching
These tests consist of existing cache tests for the CPU dispatcher,
modified for the CUDA target. These tests are based on the `TestCache`
and `TestMultiProcessCache` tests in `numba.tests.test_caching`. Any
tests that were orthogonal to the CUDA target (e.g. IPython use cases)
or irrelevant to its functionality (e.g. object mode) have been omitted.
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gmarkall committed May 30, 2022
commit cba88de760ab7064f2244869194910cf34f146f7
170 changes: 170 additions & 0 deletions numba/cuda/tests/cudapy/cache_usecases.py
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from numba import cuda
from numba.cuda.testing import CUDATestCase
import numpy as np
import sys


class UseCase:
"""
Provide a way to call a kernel as if it were a function.
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This allows the CUDA cache tests to match closely the CPU cache tests, and
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also to support calling cache use cases as njitted functions. The class
wraps a function that takes and array for the return value and arguments,
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and provides an interface that accepts arguments, launches the kernel
appropriately, and returns the stored return value.

The return type is inferred from the type of the first argument, unless it
is explicitly overridden by the ``retty`` kwarg.
"""
def __init__(self, func, retty=None):
self._func = func
self._retty = retty

def __call__(self, *args):
array_args = [np.asarray(arg) for arg in args]
if self._retty:
array_return = np.ndarray((), dtype=self._retty)
else:
array_return = np.zeros_like(array_args[0])

self._call(array_return, *array_args)
return array_return[()]

@property
def func(self):
return self._func


class CUDAUseCase(UseCase):
def _call(self, ret, *args):
self._func[1, 1](ret, *args)


@cuda.jit(cache=True)
def add_usecase_kernel(r, x, y):
r[()] = x[()] + y[()] + Z


@cuda.jit(cache=False)
def add_nocache_usecase_kernel(r, x, y):
r[()] = x[()] + y[()] + Z


add_usecase = CUDAUseCase(add_usecase_kernel)
add_nocache_usecase = CUDAUseCase(add_nocache_usecase_kernel)

Z = 1


# Inner / outer cached / uncached cases

@cuda.jit(cache=True)
def inner(x, y):
return x + y + Z


@cuda.jit(cache=True)
def outer_kernel(r, x, y):
r[()] = inner(-y[()], x[()])


@cuda.jit(cache=False)
def outer_uncached_kernel(r, x, y):
r[()] = inner(-y[()], x[()])


outer = CUDAUseCase(outer_kernel)
outer_uncached = CUDAUseCase(outer_uncached_kernel)


# Exercise returning a record instance. This used to hardcode the dtype
# pointer's value in the bitcode.

packed_record_type = np.dtype([('a', np.int8), ('b', np.float64)])
aligned_record_type = np.dtype([('a', np.int8), ('b', np.float64)], align=True)

packed_arr = np.empty(2, dtype=packed_record_type)
for i in range(packed_arr.size):
packed_arr[i]['a'] = i + 1
packed_arr[i]['b'] = i + 42.5

aligned_arr = np.array(packed_arr, dtype=aligned_record_type)


@cuda.jit(cache=True)
def record_return(r, ary, i):
r[()] = ary[i]


record_return_packed = CUDAUseCase(record_return, retty=packed_record_type)
record_return_aligned = CUDAUseCase(record_return, retty=aligned_record_type)


# Closure test cases

def make_closure(x):
@cuda.jit(cache=True)
def closure(r, y):
r[()] = x + y[()]

return CUDAUseCase(closure)


closure1 = make_closure(3)
closure2 = make_closure(5)
closure3 = make_closure(7)
closure4 = make_closure(9)


# Ambiguous / renamed functions

@cuda.jit(cache=True)
def ambiguous_function(r, x):
r[()] = x[()] + 2


renamed_function1 = CUDAUseCase(ambiguous_function)


@cuda.jit(cache=True)
def ambiguous_function(r, x):
r[()] = x[()] + 6


renamed_function2 = CUDAUseCase(ambiguous_function)


# Simple use case for multiprocessing test

@cuda.jit(cache=True)
def simple_usecase_kernel(r, x):
r[()] = x[()]


simple_usecase_caller = CUDAUseCase(simple_usecase_kernel)


class _TestModule(CUDATestCase):
"""
Tests for functionality of this module's functions.
Note this does not define any "test_*" method, instead check_module()
should be called by hand.
"""

def check_module(self, mod):
self.assertPreciseEqual(mod.add_usecase(2, 3), 6)
self.assertPreciseEqual(mod.outer_uncached(3, 2), 2)
self.assertPreciseEqual(mod.outer(3, 2), 2)

packed_rec = mod.record_return_packed(mod.packed_arr, 1)
self.assertPreciseEqual(tuple(packed_rec), (2, 43.5))
aligned_rec = mod.record_return_aligned(mod.aligned_arr, 1)
self.assertPreciseEqual(tuple(aligned_rec), (2, 43.5))

mod.simple_usecase_caller(2)


def self_test():
mod = sys.modules[__name__]
_TestModule().check_module(mod)
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