Microsoft Collective Communication Library Exector on NCCL (MSCCL-EXECUTOR-NCCL) is an inter-accelerator communication framework that is built on top of NCCL and uses its building blocks to execute custom-written collective communication algorithms.

MSCCL-EXECUTOR-NCCL is a stand-alone library of standard communication routines for GPUs, implementing all-reduce, all-gather, all-to-all, 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. MSCCL-EXECUTOR-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. To achieve this, MSCCL has multiple capabilities:

• Programmibility: Inter-connection among accelerators have different latencies and bandwidths. Therefore, a generic collective communication algorithm does not necessarily well for all topologies and buffer sizes. MSCCL-EXECUTOR-NCCL allows a user to write a hyper-optimized collective communication algorithm for a given topology and a buffer size. This is possbile through two main components: MSCCL toolkit and MSCCL-EXECUTOR-NCCL (this repo). MSCCL toolkit contains a high-level DSL (MSCCLang) and a compiler which generate an IR for the MSCCL runtime (this repo) to run on the backend. MSCCL will automatically fall back to a NCCL's generic algorithm in case there is no custom algorithm. Example provides some instances on how MSCCL toolkit with the runtime works. Please refer to MSCCL toolkit for more information.
• Profiling: MSCCL-EXECUTOR-NCCL has a profiling tool NPKit which provides detailed timeline for each primitive send and receive operation to understand the bottlenecks in a given collective communication algorithms.

To build the library :

$ git clone https://github.com/microsoft/msccl.git --recurse-submodules
$ cd msccl/executor/msccl-executor-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>

MSCCL-EXECUTOR-NCCL will be compiled and installed in build/ unless BUILDDIR is set.

By default, MSCCL-EXECUTOR-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_80,code=sm_80"

To install MSCCL-EXECUTOR-NCCL on the system, create a package then install it as root.

Debian/Ubuntu :

$ # Install tools to create debian packages
$ sudo apt install build-essential devscripts debhelper fakeroot
$ # Build MSCCL-EXECUTOR-NCCL deb package
$ make pkg.debian.build
$ ls build/pkg/deb/

RedHat/CentOS :

$ # Install tools to create rpm packages
$ sudo yum install rpm-build rpmdevtools
$ # Build MSCCL-EXECUTOR-NCCL rpm package
$ make pkg.redhat.build
$ ls build/pkg/rpm/

OS-agnostic tarball :

$ make pkg.txz.build
$ ls build/pkg/txz/

Tests for MSCCL-EXECUTOR-NCCL are maintained separately at https://github.com/Azure/msccl-tests-nccl.

$ git clone https://github.com/Azure/msccl-tests-nccl.git
$ cd msccl-tests-nccl
$ make
$ ./build/all_reduce_perf -b 8 -e 256M -f 2 -g <ngpus>

For more information on NCCL usage, please refer to the NCCL documentation.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit CLA.

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All source code and accompanying documentation is copyright (c) 2015-2022, NVIDIA CORPORATION. All rights reserved.

All modifications are copyright (c) 2022-2023, Microsoft Corporation. All rights reserved.