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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

ayulockin
ayulockin commented Dec 1, 2021

I am working on creating a WandbCallback for Weights and Biases. I am glad that CatBoost has a callback system in place but it would be great if we can extend the interface.

The current callback only supports after_iteration that takes info. Taking inspiration from XGBoost callback system it would be great if we can have before iteration that takes info, before_training, and `after

nvdbaranec
nvdbaranec commented Dec 7, 2021

Based on @karthikeyann's work on this PR rapidsai/cudf#9767 I'm wondering if it makes sense to consider removing the defaults for the stream parameters in various detail functions. It is pretty surprising how often these are getting missed.

The most common case seems to be in factory functions and various ::create functions. Maybe just do it for those?

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

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developer.nvidia.com/cuda-zone
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