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Add throughput benchmarking mode for multi-instance workload simulation #212

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c9c4130
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avolkov-intel May 13, 2026
b42d09d
Update throughput arguments and core assignment
avolkov-intel May 20, 2026
ec85b08
Update config
avolkov-intel May 20, 2026
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231 changes: 231 additions & 0 deletions configs/throughput/example.json
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Original file line number Diff line number Diff line change
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{
"INCLUDE": ["../common/sklearn.json"],
"PARAMETERS_SETS": {
"throughput settings": {
"bench": {
"num_instances": 7,
"cores_per_instance": 8,
"measurement_duration": 30
}
},
"linear regression": {
"algorithm": {
"estimator": "LinearRegression",
"estimator_params": {
"fit_intercept": true,
"copy_X": true
}
}
},
"random forest regressor": {
"algorithm": {
"estimator": "RandomForestRegressor",
"estimator_params": {
"n_estimators": 100,
"max_depth": 12,
"random_state": 42
}
}
},
"knn classifier kdtree": {
"algorithm": {
"estimator": "KNeighborsClassifier",
"estimator_params": {
"n_neighbors": 10,
"weights": "uniform",
"algorithm": "kd_tree",
"metric": "minkowski",
"p": 2
}
},
"data": {
"preprocessing_kwargs": { "normalize": "standard" }
}
},
"kmeans": {
"algorithm": {
"estimator": "KMeans",
"estimator_params": {
"n_clusters": 10,
"n_init": 1,
"max_iter": 100,
"tol": 1e-4,
"random_state": 42,
"algorithm": "lloyd"
},
"estimator_methods": {
"inference": "predict"
}
},
"data": {
"preprocessing_kwargs": { "normalize": "standard" }
}
},
"linear regression datasets": {
"data": [
{
"source": "make_regression",
"generation_kwargs": {
"n_samples": 500000,
"n_features": 50,
"n_informative": 10,
"noise": 20.0,
"random_state": 42
}
},
{
"source": "make_regression",
"generation_kwargs": {
"n_samples": 100000,
"n_features": 2000,
"n_informative": 10,
"noise": 60.0,
"random_state": 42
}
},
{
"dataset": "year_prediction_msd",
"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
},
{
"dataset": "hepmass",
"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
}
]
},
"random forest datasets": {
"data": [
{
"source": "make_regression",
"generation_kwargs": {
"n_samples": 100000,
"n_features": 20,
"n_informative": 10,
"noise": 10.0,
"random_state": 42
}
},
{
"source": "make_regression",
"generation_kwargs": {
"n_samples": 50000,
"n_features": 200,
"n_informative": 20,
"noise": 30.0,
"random_state": 42
}
},
{
"dataset": "year_prediction_msd",
"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
},
{
"dataset": "medical_charges_nominal",
"split_kwargs": { "ignore": true }
}
]
},
"knn datasets": {
"data": [
{
"source": "make_classification",
"generation_kwargs": {
"n_classes": 5,
"n_samples": 200000,
"n_features": 10,
"n_informative": 8,
"n_redundant": 2,
"n_repeated": 0,
"random_state": 42
}
},
{
"source": "make_classification",
"generation_kwargs": {
"n_classes": 5,
"n_samples": 50000,
"n_features": 50,
"n_informative": 20,
"n_redundant": 10,
"n_repeated": 0,
"random_state": 42
}
},
{
"dataset": "letters",
"split_kwargs": { "ignore": true }
},
{
"dataset": "codrnanorm",
"split_kwargs": { "ignore": true }
}
]
},
"kmeans datasets": {
"data": [
{
"source": "make_blobs",
"generation_kwargs": {
"centers": 10,
"cluster_std": 4.0,
"n_samples": 500000,
"n_features": 20,
"random_state": 42
}
},
{
"source": "make_blobs",
"generation_kwargs": {
"centers": 10,
"cluster_std": 8.0,
"n_samples": 100000,
"n_features": 200,
"random_state": 42
}
},
{
"dataset": "creditcard",
"split_kwargs": { "ignore": true }
},
{
"dataset": "hepmass",
"split_kwargs": { "train_size": 0.8, "test_size": 0.2 }
}
]
}
},
"TEMPLATES": {
"linear_regression_throughput": {
"SETS": [
"sklearn-ex[cpu] implementations",
"throughput settings",
"linear regression",
"linear regression datasets"
]
},
"random_forest_throughput": {
"SETS": [
"sklearn-ex[cpu] implementations",
"throughput settings",
"random forest regressor",
"random forest datasets"
]
},
"knn_throughput": {
"SETS": [
"sklearn-ex[cpu] implementations",
"throughput settings",
"knn classifier kdtree",
"knn datasets"
]
},
"kmeans_throughput": {
"SETS": [
"sklearn-ex[cpu] implementations",
"throughput settings",
"kmeans",
"kmeans datasets"
]
}
}
}
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