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[GR-71134] [GR-65569] Support Tunable Thresholds in Method-Hotness Classification ML Models #12726

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Merged
graalvmbot merged 1 commit into from
Dec 17, 2025
+20 −2
Merged

[GR-71134] [GR-65569] Support Tunable Thresholds in Method-Hotness Classification ML Models #12726

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22 changes: 20 additions & 2 deletions sdk/mx.sdk/mx_sdk_benchmark.py
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Original file line number Diff line number Diff line change
Expand Up @@ -888,6 +888,7 @@ def __init__(self, name, config_name, extra_java_args=None, extra_launcher_args=
self.profile_inference_call_count = False
self.force_profile_inference = False
self.profile_inference_debug = False
self.ml_callcount_threshold = None
self.analysis_context_sensitivity = None
self.optimization_level = None
self._configure_comma_separated_configs(config_name)
Expand Down Expand Up @@ -972,7 +973,15 @@ def config_name(self):
if self.profile_inference_feature_extraction is True:
config += ["profile-inference-feature-extraction"]
if self.profile_inference_call_count is True:
config += ["profile-inference-call-count"]
if self.ml_callcount_threshold is not None:
if self.ml_callcount_threshold == 0.1:
config += ["profile-inference-call-count", 'conservative']
elif self.ml_callcount_threshold == 0.7:
config += ["profile-inference-call-count", 'aggressive']
else:
mx.abort(f"Unsupported ml_callcount_threshold value: {self.ml_callcount_threshold}. Allowed values are 0.1 (conservative) or 0.7 (aggressive).")
else:
config += ["profile-inference-call-count"]
if self.pgo_instrumentation is True and self.force_profile_inference is True:
if self.pgo_exclude_conditional is True:
config += ["profile-inference-pgo"]
Expand Down Expand Up @@ -1008,7 +1017,8 @@ def _configure_from_name(self, config_name):
r'(?P<future_defaults_all>future-defaults-all-)?(?P<gate>gate-)?(?P<upx>upx-)?(?P<quickbuild>quickbuild-)?(?P<gc>g1gc-)?' \
r'(?P<llvm>llvm-)?(?P<pgo>pgo-|pgo-sampler-|pgo-perf-sampler-invoke-multiple-|pgo-perf-sampler-invoke-|pgo-perf-sampler-)?(?P<inliner>inline-)?' \
r'(?P<analysis_context_sensitivity>insens-|allocsens-|1obj-|2obj1h-|3obj2h-|4obj3h-)?(?P<jdk_profiles>jdk-profiles-collect-|adopted-jdk-pgo-)?' \
r'(?P<profile_inference>profile-inference-feature-extraction-|profile-inference-call-count-|profile-inference-pgo-|profile-inference-debug-)?(?P<sampler>safepoint-sampler-|async-sampler-)?(?P<optimization_level>O0-|O1-|O2-|O3-|Os-)?(default-)?(?P<edition>ce-|ee-)?$'
r'(?P<profile_inference>profile-inference-feature-extraction-|profile-inference-call-count-|profile-inference-call-count-conservative-|profile-inference-call-count-aggressive-|profile-inference-pgo-|profile-inference-debug-)?' \
r'(?P<sampler>safepoint-sampler-|async-sampler-)?(?P<optimization_level>O0-|O1-|O2-|O3-|Os-)?(default-)?(?P<edition>ce-|ee-)?$'

mx.logv(f"== Registering configuration: {config_name}")
match_name = f"{config_name}-" # adding trailing dash to simplify the regex
Expand Down Expand Up @@ -1156,6 +1166,12 @@ def generate_profiling_package_prefixes():
self.pgo_instrumentation = True # extract code features
elif profile_inference_config == 'profile-inference-call-count':
self.profile_inference_call_count = True
elif profile_inference_config == 'profile-inference-call-count-conservative':
self.profile_inference_call_count = True
self.ml_callcount_threshold = 0.1
elif profile_inference_config == 'profile-inference-call-count-aggressive':
self.profile_inference_call_count = True
self.ml_callcount_threshold = 0.7
elif profile_inference_config == "profile-inference-pgo":
# We need to run instrumentation as the profile-inference-pgo JVM config requires dynamically collected
# profiles to combine with the ML-inferred branch probabilities.
Expand Down Expand Up @@ -1832,6 +1848,8 @@ def run_stage_image(self):
dump_file_flag))
elif self.profile_inference_call_count:
ml_args = svm_experimental_options(['-H:+MLCallCountProfileInference'])
if self.ml_callcount_threshold is not None:
ml_args += svm_experimental_options([f'-H:MLCallCountProfileInferenceClassificationThreshold={self.ml_callcount_threshold:.2f}'])
elif self.force_profile_inference:
ml_args = svm_experimental_options(['-H:+MLGraphFeaturesExtraction', '-H:+MLProfileInference'])
else:
Expand Down