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# benchmark registry
import os
def tokwargs(**kwargs): return kwargs
INSTALL_PREFIX = '/opt/usr'
GRAS_ENV = {
'PATH': os.path.join(INSTALL_PREFIX, 'gras/bin:$PATH:%s'%os.getenv('PATH')),
'LD_LIBRARY_PATH': os.path.join(INSTALL_PREFIX, 'gras/lib:%s'%os.getenv('LD_LIBRARY_PATH')),
'PYTHONPATH': os.path.join(INSTALL_PREFIX, 'gras/lib/python2.7/dist-packages:%s'%os.getenv('PYTHONPATH')),
}
GR_ENV = {
'PATH': os.path.join(INSTALL_PREFIX, 'gr/bin:$PATH:%s'%os.getenv('PATH')),
'LD_LIBRARY_PATH': os.path.join(INSTALL_PREFIX, 'gr/lib:%s'%os.getenv('LD_LIBRARY_PATH')),
'PYTHONPATH': os.path.join(INSTALL_PREFIX, 'gr/lib/python2.7/dist-packages:%s'%os.getenv('PYTHONPATH')),
}
BENCHMARK_MANY_11_BLOCKS = tokwargs(
wat='Benchmark the schedulers with many 1:1 ratio blocks',
moar='''\
- Compare simultaneous 1:1 ratio blocks in each scheduler.
- GRAS will use only the buffer pool allocator,
and every work will fully consume available buffers.''',
tests = [
tokwargs(wat='GRAS', args=['tb_many_1_to_1_blocks.py', '1e8'], env=GRAS_ENV),
tokwargs(wat='GR', args=['tb_many_1_to_1_blocks.py', '1e8'], env=GR_ENV),
],
to_result = lambda t: 1e8/t
)
BENCHMARK_MANY_RATE_BLOCKS = tokwargs(
wat='Benchmark the schedulers with many rate changing blocks',
moar='''\
- Compare simultaneous changing ratio blocks in each scheduler.
- GRAS will use only the buffer pool allocator,
and every work will fully consume available buffers.''',
tests = [
tokwargs(wat='GRAS', args=['tb_many_rate_changes.py', '1e4'], env=GRAS_ENV),
tokwargs(wat='GR', args=['tb_many_rate_changes.py', '1e4'], env=GR_ENV),
],
to_result = lambda t: 1e4/t
)
BENCHMARK_FILTER_BLOCK = tokwargs(
wat='Benchmark the schedulers with a filter block',
moar='''\
- Compare filter blocks in each scheduler.
- Shows both schedulers using circular buffer.
- The decimating FIR filter is compared.
- The rational resampler filter is compared.''',
tests = [
tokwargs(wat='GRAS decim FIR', args=['tb_filter_block.py', '--num', '1e7', '--which', 'dfir'], env=GRAS_ENV),
tokwargs(wat='GR decim FIR', args=['tb_filter_block.py', '--num', '1e7', '--which', 'dfir'], env=GR_ENV),
tokwargs(wat='GRAS resampler', args=['tb_filter_block.py', '--num', '1e7', '--which', 'resamp'], env=GRAS_ENV),
tokwargs(wat='GR resampler', args=['tb_filter_block.py', '--num', '1e7', '--which', 'resamp'], env=GR_ENV),
],
to_result = lambda t: 1e7/t
)
BENCHMARK_MATH_OPS = tokwargs(
wat='Benchmark GrExtras vs gr-blocks math blocks',
moar='''\
- Compare math block implementations using GRAS.
- All blocks are using vector optimization.
- GrExtras math blocks avoid an unnecessary memcpy.
- GrExtras math blocks enable automatic bufer in-placing.''',
tests = [
tokwargs(wat='GrExtras Add\n(GRAS)', args=['tb_grextras_math.py', '1e8', 'extras_add'], env=GRAS_ENV),
tokwargs(wat='gr-blocks Add\n(GRAS)', args=['tb_grextras_math.py', '1e8', 'blocks_add'], env=GRAS_ENV),
tokwargs(wat='gr-blocks Add\n(GR)', args=['tb_grextras_math.py', '1e8', 'blocks_add'], env=GR_ENV),
tokwargs(wat='GrExtras Mult\n(GRAS)', args=['tb_grextras_math.py', '1e8', 'extras_mult'], env=GRAS_ENV),
tokwargs(wat='gr-blocks Mult\n(GRAS)', args=['tb_grextras_math.py', '1e8', 'blocks_mult'], env=GRAS_ENV),
tokwargs(wat='gr-blocks Mult\n(GR)', args=['tb_grextras_math.py', '1e8', 'blocks_mult'], env=GR_ENV),
],
to_result = lambda t: 1e8/t
)
BENCHMARK_DELAY_BLOCKS = tokwargs(
wat='Benchmark GrExtras vs gr-core delay block',
moar='''\
- Compare delay block implementations using GRAS.
- The GrExtras implementation uses zero-copy.''',
tests = [
tokwargs(wat='GrExtras Delay\n(GRAS)', args=['tb_grextras_delay.py', '1e8', 'extras_delay'], env=GRAS_ENV),
tokwargs(wat='gr-core Delay\n(GRAS)', args=['tb_grextras_delay.py', '1e8', 'core_delay'], env=GRAS_ENV),
tokwargs(wat='gr-core Delay\n(GR)', args=['tb_grextras_delay.py', '1e8', 'core_delay'], env=GR_ENV),
],
to_result = lambda t: 1e8/t
)
BENCHMARKS = (
BENCHMARK_MANY_11_BLOCKS,
BENCHMARK_MANY_RATE_BLOCKS,
BENCHMARK_FILTER_BLOCK,
BENCHMARK_MATH_OPS,
BENCHMARK_DELAY_BLOCKS,
)
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