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March 31, 2020 19:40
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test CUB kernels
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| import sys | |
| import warnings | |
| warnings.filterwarnings("ignore", category=FutureWarning) | |
| import numpy as np | |
| import cupy as cp | |
| from cupyx.time import repeat | |
| shape = (256, 512, 512) | |
| a = cp.random.random(shape) | |
| a_np = cp.asnumpy(a) | |
| CUB_supported = ['sum', 'prod', 'min', 'max', 'argmin', 'argmax'] | |
| REST = ['amin', 'amax', 'nanmin', 'nanmax', 'nanargmin', 'nanargmax', | |
| 'mean', 'nanmean', 'var', 'nanvar', 'nansum', 'nanprod', | |
| 'all', 'any', 'count_nonzero'] | |
| for reduce_func in CUB_supported + REST: | |
| for axis in [(2,), (1, 2), (0, 1, 2)]: # [(0,1,2)]: | |
| print("testing", reduce_func, "with axis = ", axis, '...') | |
| func = getattr(cp, reduce_func) | |
| # get numpy answer for comparison | |
| if reduce_func not in ('argmin', 'argmax', 'nanargmin', 'nanargmax'): | |
| ans = getattr(np, reduce_func)(a_np, axis) | |
| elif len(axis) == 1: | |
| ans = getattr(np, reduce_func)(a_np, axis[0]) | |
| else: | |
| ans = None | |
| cp.cuda.cub_enabled = False | |
| cp.core.cub_block_reduction_enabled = False | |
| data = repeat(func, (a, axis), n=100) | |
| results = [data._to_str_per_item('GPU', data.gpu_times)] | |
| print('{:<10s} (old kernel):{}'.format(reduce_func, ' '.join(results))) | |
| b = func(a, axis) | |
| if reduce_func in CUB_supported: | |
| cp.cuda.cub_enabled = True | |
| cp.core.cub_block_reduction_enabled = False | |
| data = repeat(func, (a, axis), n=100) | |
| results = [data._to_str_per_item('GPU', data.gpu_times)] | |
| print('{:<10s} (CUB device):{}'.format(reduce_func, ' '.join(results))) | |
| c = func(a, axis) | |
| else: | |
| print('{:<10s} (CUB device):{}'.format(reduce_func, ' (CUB device-wide reduction not available)')) | |
| c = None | |
| cp.cuda.cub_enabled = False | |
| cp.core.cub_block_reduction_enabled = True | |
| data = repeat(func, (a, axis), n=100) | |
| results = [data._to_str_per_item('GPU', data.gpu_times)] | |
| print('{:<10s} (CUB blocks):{}'.format(reduce_func, ' '.join(results))) | |
| d = func(a, axis) | |
| try: | |
| cp.cuda.cub_enabled = False | |
| cp.core.cub_block_reduction_enabled = False | |
| if ans is not None: | |
| assert cp.allclose(ans, b) | |
| if c is not None: | |
| assert cp.allclose(ans, c) | |
| assert cp.allclose(ans, d) | |
| except AssertionError: | |
| print("Result not match! (function: {}, axis: {})".format(reduce_func, axis), file=sys.stderr) | |
| raise | |
| finally: | |
| print() |
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CUDA 10.0 + GTX 2080 Ti: