NCCL alternatives and similar libraries
Based on the "Concurrency" category.
Alternatively, view NCCL alternatives based on common mentions on social networks and blogs.
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moodycamel
A fast multi-producer, multi-consumer lock-free concurrent queue for C++11 -
Taskflow
A General-purpose Parallel and Heterogeneous Task Programming System -
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readerwriterqueue
A fast single-producer, single-consumer lock-free queue for C++ -
C++ Actor Framework
An Open Source Implementation of the Actor Model in C++ -
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ck
Concurrency primitives, safe memory reclamation mechanisms and non-blocking (including lock-free) data structures designed to aid in the research, design and implementation of high performance concurrent systems developed in C99+. -
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MPMCQueue.h
A bounded multi-producer multi-consumer concurrent queue written in C++11 -
RaftLib
The RaftLib C++ library, streaming/dataflow concurrency via C++ iostream-like operators -
VexCL
VexCL is a C++ vector expression template library for OpenCL/CUDA/OpenMP -
continuable
C++14 asynchronous allocation aware futures (supporting then, exception handling, coroutines and connections) -
SPSCQueue.h
A bounded single-producer single-consumer wait-free and lock-free queue written in C++11 -
A C++14 library for executors
C++ library for executors -
Bolt
Bolt is a C++ template library optimized for GPUs. Bolt provides high-performance library implementations for common algorithms such as scan, reduce, transform, and sort. -
xenium
A C++ library providing various concurrent data structures and reclamation schemes. -
thread-pool
A modern, fast, lightweight thread pool library based on C++20 -
CUB
THIS REPOSITORY HAS MOVED TO github.com/nvidia/cub, WHICH IS AUTOMATICALLY MIRRORED HERE. -
SObjectizer
SObjectizer: it's all about in-process message dispatching! -
Light Actor Framework
Laughably simple yet effective Actor concurrency framework for C++20 -
BlockingCollection
C++11 thread safe, multi-producer, multi-consumer blocking queue, stack & priority queue class -
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Easy Creation of GnuPlot Scripts from C++
A simple C++17 lib that helps you to quickly plot your data with GnuPlot -
alpaka
The project alpaka has moved to https://github.com/alpaka-group/alpaka -
TestGPT | Generating meaningful tests for busy devs
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
NCCL
Optimized primitives for inter-GPU communication.
Introduction
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.
Build
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 build/ unless 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"
Install
To install 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 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 NCCL rpm package
$ make pkg.redhat.build
$ ls build/pkg/rpm/
OS-agnostic tarball :
$ make pkg.txz.build
$ ls build/pkg/txz/
Tests
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>
Copyright
All source code and accompanying documentation is copyright (c) 2015-2020, NVIDIA CORPORATION. All rights reserved.