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Posted to discuss-archive@tvm.apache.org by Jeremiah Morrill via TVM Discuss <no...@discuss.tvm.ai> on 2019/11/12 19:26:48 UTC
[TVM Discuss] [Questions] XGBoost's cuda acceleration
It seems [XGBoost supports GPU acceleration](http://tracking.discuss.tvm.ai/tracking/click?d=16FMB7EwcxvJDCA2R-NliyJmm7vGiGsXVdu32-HbyXzgzHrax6cTTZF8vPk3tcPUdOYhHHQGI8McfylgvP47UvwPiIJFsNZq28iWJAHqZiWQAUNj2QyjvxwXmLYmOoAbUc_Qx_XPrgLlsOX54dR0pLn7p1ZfVXr664BMoqjouLIT0) via cuda (9?) with the `gpu_hist` parameter to `xgb_params`
In xgboost_code_model.py I added: '`tree_method`': '`gpu_hist`' and ran a few tests (16 core, 1080gtx)
**WITH '`gpu_hist`'**
**First run:**
`[Task 1/42] Current/Best: 178.70/2169.96 GFLOPS | Progress: (256/256) | 901.07 s Done.`
**Second run:**
`[Task 1/42] Current/Best: 1669.95/1804.79 GFLOPS | Progress: (256/256) | 904.57 s Done.`
**WITHOUT '`gpu_hist`'**
**First run:**
`[Task 1/42] Current/Best: 48.44/1714.60 GFLOPS | Progress: (256/256) | 980.04 s Done.`
**Second Run:**
`[Task 1/42] Current/Best: 113.77/1672.49 GFLOPS | Progress: (256/256) | 1038.44 s Done.`
Even though I only run each test twice, you do see the '`gpu_hist`' does complete a bit faster.
I did see the cuda usage on my GPU use about 2 - 4% when running the xgboost cost model.
Is this something that should be exposed in the public API or was there a reason why it was excluded?
Can someone else verify benefit?
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Tianqi Chen, UW, Seattle, WA, 98105, United States
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