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limit benchmark-based usage factors #4803

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limit benchmark-based usage factors #4803

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16 changes: 13 additions & 3 deletions golem/marketplace/wasm_marketplace.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,8 +25,11 @@
logger = logging.getLogger(__name__)


USAGE_SECOND = 1e9 # usage is measured in nanoseconds


class RequestorWasmMarketStrategy(RequestorPoolingMarketStrategy):
DEFAULT_USAGE_BENCHMARK: float = 1.0
DEFAULT_USAGE_BENCHMARK: float = 1.0 * USAGE_SECOND

_usages: ClassVar[Dict[str, float]] = dict()
_usage_factors: ClassVar[Dict[str, float]] = dict()
Expand All @@ -39,6 +42,8 @@ def get_my_usage_benchmark(cls) -> float:

@classmethod
def set_my_usage_benchmark(cls, benchmark: float) -> None:
if benchmark < 1e-6 * USAGE_SECOND:
benchmark = cls.DEFAULT_USAGE_BENCHMARK
logger.info("RWMS: set_my_usage_benchmark %.3f", benchmark)
cls._my_usage_benchmark = benchmark

Expand All @@ -49,8 +54,13 @@ def get_usage_factor(cls, provider_id, usage_benchmark):
# Division goes this way since higher benchmark val means
# faster processor
usage_factor = cls.get_my_usage_benchmark() / usage_benchmark
if not usage_factor:
usage_factor = 1.0

# Sanity check against misreported benchmarks
usage_factor = min(max(usage_factor, 0.25), 1.5)
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why are we assuming that the usage cannot be farther away than that from our own? can't a really slow or really fast CPU have such - out of range - results?

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It can, but if it is, it will be caught by the usage factor adjustment. It may make sense to widen the limits though.

logger.info("RWMS: initial usage factor for %s = %.3f",
provider_id,
usage_factor)

cls._usage_factors[provider_id] = usage_factor
return usage_factor

Expand Down
16 changes: 12 additions & 4 deletions tests/golem/marketplace/test_wasm_marketplace.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,8 @@
from golem.marketplace import ProviderPerformance
from golem.marketplace.wasm_marketplace import RequestorWasmMarketStrategy

USAGE_SECOND = 1e9 # usage is measured in nanoseconds


class TestOfferChoice(TestCase):
TASK_1 = 'task_1'
Expand All @@ -21,23 +23,29 @@ def setUp(self):
mock_offer_1.quality = (.0, .0, .0, .0)
mock_offer_1.reputation = .0
mock_offer_1.price = 5.0
mock_offer_1.provider_performance = ProviderPerformance(1000 / 1.25)
mock_offer_1.provider_performance = ProviderPerformance(
1 * USAGE_SECOND / 1.25)
self.mock_offer_1 = mock_offer_1

mock_offer_2 = Mock()
mock_offer_2.provider_id = self.PROVIDER_2
mock_offer_2.quality = (.0, .0, .0, .0)
mock_offer_2.reputation = .0
mock_offer_2.price = 6.0
mock_offer_2.provider_performance = ProviderPerformance(1000 / 0.8)
mock_offer_2.provider_performance = ProviderPerformance(
1 * USAGE_SECOND / 0.8)
self.mock_offer_2 = mock_offer_2

def test_get_usage_benchmark(self):
self.assertEqual(
RequestorWasmMarketStrategy.get_my_usage_benchmark(), 1.0
RequestorWasmMarketStrategy.get_my_usage_benchmark(),
RequestorWasmMarketStrategy.DEFAULT_USAGE_BENCHMARK
)
self.assertEqual(
RequestorWasmMarketStrategy.get_usage_factor(self.PROVIDER_1, 1.0),
RequestorWasmMarketStrategy.get_usage_factor(
self.PROVIDER_1,
RequestorWasmMarketStrategy.DEFAULT_USAGE_BENCHMARK
),
1.0
)

Expand Down