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point-in-rbbox

功能

实现point-in-rbbox算子(支持CUDA和Triton),用于计算3D旋转框内的点云,相比PyTorch版本显存有明显优化

依赖

  • CUDA:11.8
  • PyTorch:2.0.0
  • Triton:2.0.0(使用Triton算子时需要)

安装

  • pip安装
export TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6 8.9 9.0+PTX" # 支持不同GPU架构【可选】
export ENABLE_BF16=1 # 支持BF16【可选,部分GPU可能不支持】
python3 -m pip install points-in-rbbox
  • 源码安装
git clone https://github.com/lh9171338/points-in-rbbox.git
cd points-in-rbbox

export TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6 8.9 9.0+PTX" # 支持不同GPU架构【可选】
export ENABLE_BF16=1 # 支持BF16【可选,部分GPU可能不支持】
python3 setup.py install

使用

  • CUDA算子
from points_in_rbbox import points_in_rbbox_cuda

mask = points_in_rbbox_cuda(points, boxes)
  • Triton算子(无需编译,自动适配GPU架构)
from points_in_rbbox import points_in_rbbox_triton

mask = points_in_rbbox_triton(points, boxes)

显存&耗时

方法 dtype 显存(GB) 耗时(s)
points_in_rbbox_torch FP32 10.0 12
points_in_rbbox_torch FP16 5.3 10
points_in_rbbox_torch BF16 5.3 10
points_in_rbbox_cuda FP32 1.2 9
points_in_rbbox_cuda FP16 1.0 9
points_in_rbbox_cuda BF16 1.0 9
points_in_rbbox_triton FP32 1.2 8
points_in_rbbox_triton FP16 1.0 8
points_in_rbbox_triton BF16 1.0 8

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