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Use single precision in gain calculation, use pointers instead of span. #8051

Merged
merged 1 commit into from
Jul 12, 2022
Merged

Use single precision in gain calculation, use pointers instead of span. #8051

merged 1 commit into from
Jul 12, 2022

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RAMitchell
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Removing spans in favour of raw pointers decreases register pressure in the GPU kernel significantly.

Use of double/single precision in gain calculations is inconsistent. Prefer single precision.

@trivialfis
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Do you have some benchmarks for accuracy for small datasets? Preferably with CPU implementation as well.

@RAMitchell
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Here are 2 gbm-bench runs for both CPU and GPU. The accuracies are identical.

Before PR 
{
"airline": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.8434307346593626,
      "Accuracy": 0.7182532274977227,
      "Log_Loss": 0.5297073384219716,
      "Precision": 0.6536453477079318,
      "Recall": 0.8642811257864607
    },
    "train_time": 966.4464671728201,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.8431610435789277,
      "Accuracy": 0.718068859889482,
      "Log_Loss": 0.5300302877835903,
      "Precision": 0.6534910973662341,
      "Recall": 0.8641185139771076
    },
    "train_time": 91.14509701775387,
    "train_time_std": 0.0
  }
},
"bosch": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.6902547809021118,
      "Accuracy": 0.955129883843717,
      "Log_Loss": 0.24913303252016256,
      "Precision": 0.04193227091633466,
      "Recall": 0.29543859649122806
    },
    "train_time": 57.79425460193306,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.6911762239977932,
      "Accuracy": 0.9580316789862724,
      "Log_Loss": 0.24111224289242209,
      "Precision": 0.04423262289814715,
      "Recall": 0.28982456140350876
    },
    "train_time": 12.88072164868936,
    "train_time_std": 0.0
  }
},
"covtype": {
  "xgb-cpu": {
    "accuracy": {
      "Accuracy": 0.9398466476769103,
      "F1": 0.9397222738018455,
      "Precision": 0.9398793000566292,
      "Recall": 0.9398466476769103
    },
    "train_time": 39.06878037704155,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "Accuracy": 0.9379620147500495,
      "F1": 0.9378270737037167,
      "Precision": 0.9380157400229653,
      "Recall": 0.9379620147500495
    },
    "train_time": 18.243315340019763,
    "train_time_std": 0.0
  }
},
"epsilon": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.9477093412445664,
      "Accuracy": 0.87034,
      "Log_Loss": 0.3009770990117234,
      "Precision": 0.8434001151196687,
      "Recall": 0.9092783505154639
    },
    "train_time": 1550.9631590410136,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.9481207911778409,
      "Accuracy": 0.87118,
      "Log_Loss": 0.2998701572805944,
      "Precision": 0.8448715324936278,
      "Recall": 0.9090381343208888
    },
    "train_time": 46.500129331834614,
    "train_time_std": 0.0
  }
},
"fraud": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.9654261008004777,
      "Accuracy": 0.9995611109160493,
      "Log_Loss": 0.003519674551653179,
      "Precision": 0.9506172839506173,
      "Recall": 0.7857142857142857
    },
    "train_time": 2.6741700717248023,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.965037059421405,
      "Accuracy": 0.9995611109160493,
      "Log_Loss": 0.00356269826075694,
      "Precision": 0.9397590361445783,
      "Recall": 0.7959183673469388
    },
    "train_time": 1.332988286856562,
    "train_time_std": 0.0
  }
},
"higgs": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.8399291373085628,
      "Accuracy": 0.7342790909090909,
      "Log_Loss": 0.5217814797614634,
      "Precision": 0.6912109500847503,
      "Recall": 0.9014453459278047
    },
    "train_time": 112.69107929291204,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.8393949180683775,
      "Accuracy": 0.7335804545454545,
      "Log_Loss": 0.5225674019070321,
      "Precision": 0.6904788642120271,
      "Recall": 0.9015628188704419
    },
    "train_time": 17.52672170335427,
    "train_time_std": 0.0
  }
},
"year": {
  "xgb-cpu": {
    "accuracy": {
      "MeanAbsError": 6.220576286315918,
      "MeanSquaredError": 79.77742004394531,
      "MedianAbsError": 4.271484375
    },
    "train_time": 16.023101320955902,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "MeanAbsError": 6.22576379776001,
      "MeanSquaredError": 79.91011810302734,
      "MedianAbsError": 4.2696533203125
    },
    "train_time": 6.9804930170066655,
    "train_time_std": 0.0
  }
}
}
After PR 
{
"airline": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.8434307346593626,
      "Accuracy": 0.7182532274977227,
      "Log_Loss": 0.5297073384219716,
      "Precision": 0.6536453477079318,
      "Recall": 0.8642811257864607
    },
    "train_time": 994.9771266668104,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.8431610435789277,
      "Accuracy": 0.718068859889482,
      "Log_Loss": 0.5300302877835903,
      "Precision": 0.6534910973662341,
      "Recall": 0.8641185139771076
    },
    "train_time": 89.69093904690817,
    "train_time_std": 0.0
  }
},
"bosch": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.6902547809021118,
      "Accuracy": 0.955129883843717,
      "Log_Loss": 0.24913303252016256,
      "Precision": 0.04193227091633466,
      "Recall": 0.29543859649122806
    },
    "train_time": 55.15471205022186,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.6911762239977932,
      "Accuracy": 0.9580316789862724,
      "Log_Loss": 0.24111224289242209,
      "Precision": 0.04423262289814715,
      "Recall": 0.28982456140350876
    },
    "train_time": 12.608841334935278,
    "train_time_std": 0.0
  }
},
"covtype": {
  "xgb-cpu": {
    "accuracy": {
      "Accuracy": 0.9398466476769103,
      "F1": 0.9397222738018455,
      "Precision": 0.9398793000566292,
      "Recall": 0.9398466476769103
    },
    "train_time": 40.34531668201089,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "Accuracy": 0.9379620147500495,
      "F1": 0.9378270737037167,
      "Precision": 0.9380157400229653,
      "Recall": 0.9379620147500495
    },
    "train_time": 17.709761895705014,
    "train_time_std": 0.0
  }
},
"epsilon": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.9477093412445664,
      "Accuracy": 0.87034,
      "Log_Loss": 0.3009770990117234,
      "Precision": 0.8434001151196687,
      "Recall": 0.9092783505154639
    },
    "train_time": 1647.445112537127,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.9481207911778409,
      "Accuracy": 0.87118,
      "Log_Loss": 0.2998701572805944,
      "Precision": 0.8448715324936278,
      "Recall": 0.9090381343208888
    },
    "train_time": 45.50282173091546,
    "train_time_std": 0.0
  }
},
"fraud": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.9654261008004777,
      "Accuracy": 0.9995611109160493,
      "Log_Loss": 0.003519674551653179,
      "Precision": 0.9506172839506173,
      "Recall": 0.7857142857142857
    },
    "train_time": 2.592053124215454,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.965037059421405,
      "Accuracy": 0.9995611109160493,
      "Log_Loss": 0.00356269826075694,
      "Precision": 0.9397590361445783,
      "Recall": 0.7959183673469388
    },
    "train_time": 1.2642242829315364,
    "train_time_std": 0.0
  }
},
"higgs": {
  "xgb-cpu": {
    "accuracy": {
      "AUC": 0.8399291373085628,
      "Accuracy": 0.7342790909090909,
      "Log_Loss": 0.5217814797614634,
      "Precision": 0.6912109500847503,
      "Recall": 0.9014453459278047
    },
    "train_time": 109.59541429579258,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "AUC": 0.8393949180683775,
      "Accuracy": 0.7335804545454545,
      "Log_Loss": 0.5225674019070321,
      "Precision": 0.6904788642120271,
      "Recall": 0.9015628188704419
    },
    "train_time": 17.26801946386695,
    "train_time_std": 0.0
  }
},
"year": {
  "xgb-cpu": {
    "accuracy": {
      "MeanAbsError": 6.220576286315918,
      "MeanSquaredError": 79.77742004394531,
      "MedianAbsError": 4.271484375
    },
    "train_time": 17.15528222732246,
    "train_time_std": 0.0
  },
  "xgb-gpu": {
    "accuracy": {
      "MeanAbsError": 6.22576379776001,
      "MeanSquaredError": 79.91011810302734,
      "MedianAbsError": 4.2696533203125
    },
    "train_time": 6.902157460339367,
    "train_time_std": 0.0
  }
}
}

@trivialfis
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It's weird that the CPU implementation seems somehow slower.

@RAMitchell
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I wouldn't read too much into it. The CPU runs have very high variance on my dual socket machine.

@RAMitchell RAMitchell merged commit 0bdaca2 into dmlc:master Jul 12, 2022
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@RAMitchell @trivialfis