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CUDA

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CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.

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numba
rhjmoore
rhjmoore commented Sep 1, 2021

I see comments suggesting adding this to understand how loops are being handled by numba, and in the their own FAQ (https://numba.pydata.org/numba-doc/latest/user/faq.html)

from llvmlite import binding as llvm
llvm.set_option('','--debug-only=loop-vectorize')

You would then create your njit function and run it, and I believe the idea is that it prints debug information about whether

nickhuangxinyu
nickhuangxinyu commented Sep 25, 2021

usually, after trained model. i save model in cpp format with code:

cat_model.save_model('a', format="cpp")
cat_model.save_model('b', format="cpp")

but when my cpp need to use multi models.

in my main.cpp

#include "a.hpp"
#include "b.hpp"

int main() {
  // do something
  double a_pv = ApplyCatboostModel({1.2, 2.3});  // i want to a.hpp's model here
  double b_pv 
thrust
wphicks
wphicks commented Feb 8, 2021

Report needed documentation

Report needed documentation
While the estimator guide offers a great breakdown of how to use many of the tools in api_context_managers.py, it would be helpful to have information right in the docstring during development to more easily understand what is actually going on in each of the provided functions/classes/methods. This is particularly important for

Created by Nvidia

Released June 23, 2007

Website
developer.nvidia.com/cuda-zone
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