# This file created by conda-build 24.3.0
# meta.yaml template originally from:
# /home/conda/recipe_root, last modified Thu Apr  4 20:30:29 2024
# ------------------------------------------------

package:
  name: nccl
  version: 2.21.5.1
source:
  patches:
    - 0001-Allow-custom-NVCC-path.patch
  sha256: 1923596984d85e310b5b6c52b2c72a1b93da57218f2bc5a5c7ac3d59297a3303
  url: https://github.com/NVIDIA/nccl/archive/v2.21.5-1.tar.gz
build:
  ignore_run_exports_from:
    - nvcc_linux-64 11.8.*
  number: '0'
  run_exports:
    - nccl >=2.21.5.1,<3.0a0
  string: h6103f9b_0
requirements:
  build:
    - _libgcc_mutex 0.1 conda_forge
    - _openmp_mutex 4.5 2_gnu
    - _sysroot_linux-64_curr_repodata_hack 3 h69a702a_14
    - binutils_impl_linux-64 2.40 hf600244_0
    - binutils_linux-64 2.40 hdade7a5_3
    - gcc_impl_linux-64 11.4.0 h7aa1c59_5
    - gcc_linux-64 11.4.0 h0f0c6b6_3
    - gxx_impl_linux-64 11.4.0 h7aa1c59_5
    - gxx_linux-64 11.4.0 h2730b16_3
    - kernel-headers_linux-64 3.10.0 h4a8ded7_14
    - ld_impl_linux-64 2.40 h41732ed_0
    - libgcc-devel_linux-64 11.4.0 h922705a_105
    - libgcc-ng 13.2.0 h807b86a_5
    - libgomp 13.2.0 h807b86a_5
    - libsanitizer 11.4.0 h4dcbe23_5
    - libstdcxx-devel_linux-64 11.4.0 h922705a_105
    - libstdcxx-ng 13.2.0 h7e041cc_5
    - make 4.3 hd18ef5c_1
    - nvcc_linux-64 11.8 h41dc85b_23
    - sed 4.8 he412f7d_0
    - sysroot_linux-64 2.17 h4a8ded7_14
  host:
    - _libgcc_mutex 0.1 conda_forge
    - _openmp_mutex 4.5 2_gnu
    - cuda-version 11.8 h70ddcb2_3
    - libgcc-ng 13.2.0 h807b86a_5
    - libgomp 13.2.0 h807b86a_5
    - libstdcxx-ng 13.2.0 h7e041cc_5
  run:
    - cuda-version >=11.8,<12.0a0
    - libgcc-ng >=12
    - libstdcxx-ng >=12
test:
  commands:
    - test -f "${PREFIX}/include/nccl.h"
    - test -f "${PREFIX}/lib/libnccl.so"
    - test ! -f "${PREFIX}/lib/libnccl_static.a"
about:
  description: 'The NVIDIA Collective Communications Library (NCCL) implements multi-GPU

    and multi-node collective communication primitives that are performance

    optimized for NVIDIA GPUs. NCCL provides routines such as all-gather,

    all-reduce, broadcast, reduce, reduce-scatter, that are optimized to

    achieve high bandwidth over PCIe and NVLink high-speed interconnect.

    '
  dev_url: https://github.com/NVIDIA/nccl
  doc_url: https://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/docs/index.html
  home: https://developer.nvidia.com/nccl
  license: BSD-3-Clause
  license_family: BSD
  license_file: LICENSE.txt
  summary: Optimized primitives for collective multi-GPU communication
extra:
  copy_test_source_files: true
  final: true
  flow_run_id: azure_20240404.2.1
  recipe-maintainers:
    - jakirkham
    - leofang
  remote_url: https://github.com/conda-forge/nccl-feedstock
  sha: 00bcea123d713ebf2724425072049de50bb7523e
