Optimized primitives for inter-GPU communication.
NCCL (pronounced "Nickel") is a stand-alone library of standard communication routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast, reduce-scatter, as well as any send/receive based communication pattern. It has been optimized to achieve high bandwidth on platforms using PCIe, NVLink, NVswitch, as well as networking using InfiniBand Verbs or TCP/IP sockets. NCCL supports an arbitrary number of GPUs installed in a single node or across multiple nodes, and can be used in either single- or multi-process (e.g., MPI) applications.
For more information on NCCL usage, please refer to the NCCL documentation.
Note: the official and tested builds of NCCL can be downloaded from: https://developer.nvidia.com/nccl. You can skip the following build steps if you choose to use the official builds.
To build the library :
$ cd nccl $ make -j src.build
If CUDA is not installed in the default /usr/local/cuda path, you can define the CUDA path with :
$ make src.build CUDA_HOME=<path to cuda install>
NCCL will be compiled and installed in
BUILDDIR is set.
By default, NCCL is compiled for all supported architectures. To accelerate the compilation and reduce the binary size, consider redefining
NVCC_GENCODE (defined in
makefiles/common.mk) to only include the architecture of the target platform :
$ make -j src.build NVCC_GENCODE="-gencode=arch=compute_70,code=sm_70"
To install NCCL on the system, create a package then install it as root.
$ # Install tools to create debian packages $ sudo apt install build-essential devscripts debhelper fakeroot $ # Build NCCL deb package $ make pkg.debian.build $ ls build/pkg/deb/
$ # Install tools to create rpm packages $ sudo yum install rpm-build rpmdevtools $ # Build NCCL rpm package $ make pkg.redhat.build $ ls build/pkg/rpm/
OS-agnostic tarball :
$ make pkg.txz.build $ ls build/pkg/txz/
Tests for NCCL are maintained separately at https://github.com/nvidia/nccl-tests.
$ git clone https://github.com/NVIDIA/nccl-tests.git $ cd nccl-tests $ make $ ./build/all_reduce_perf -b 8 -e 256M -f 2 -g <ngpus>
All source code and accompanying documentation is copyright (c) 2015-2020, NVIDIA CORPORATION. All rights reserved.