178b6b7590
Rework core for NVIDIA Trusted Computing * Compress work structs so that they are shared between channels * Utilize the full amount of kernel argument space permitted (4k) before resorting to work fifo. * Rework the task preprocessing phase. * Use a separate abortDevFlag which is kept in sync with abortFlag using cudaMemcpy operations. * Rename src/include/align.h to src/include/bitops.h Add lazy connection establishment for collective operations * Move buffer allocation and connection establishment to the first collective operation using that algorithm. * Accelerate init time and reduce memory usage. * Avoid allocating NVLS buffers if all calls are registered. * Compute algo/proto in ncclLaunchCollTasksInfo early on. * Connect peers in ncclCollPreconnectFunc if not connected already. * Also move shared buffer creation to the first send/recv call. Accelerate intra-node NVLink detection * Make each rank only detect NVLinks attached to its GPU. * Fuse XMLs to reconstruct the full NVLink topology Add init profiling to report time spend in different init phases. * Report timings of bootstrap, allgather, search, connect, etc. * Add new "PROFILE" category for NCCL_DEBUG_SUBSYS. Add support for PCI p2p on split PCI switches * Detect split PCI switches through a kernel module exposing switch information. * Update the topology XML and graph to add those inter-switch connections. Add cost estimation API * Add a new ncclGroupEndSimulate primitive to return the estimated time a group would take. Net/IB: Add separate traffic class for fifo messages * Add NCCL_IB_FIFO_TC to control the traffic class of fifo messages independently from NCCL_IB_TC. Merges PR #1194 Net/IB: Add support for IB router * Use flid instead of lid if subnets do not match * Warn if flid is 0 Optimizations and fixes for device network offload (unpack) * Double the default number of channels * Cache netDeviceType * Fix save/increment head logic to enable Tree support. Support ncclGroupStart/End for ncclCommAbort/Destroy * Allow Abort/Destroy to be called within a group when managing multiple GPUs with a single process. Improve Tuner API * Provide to the plugin the original cost table so that the plugin can leave unknown or disabled algo/proto combinations untouched. * Remove nvlsSupport and collnetSupport. Do not print version to stdout when using a debug file * Also print version from all processes with INFO debug level. Fixes issue #1271 Fix clang warnings in NVTX headers * Update NVTX headers to the latest version Fixes issue #1270 Disable port fusion in heterogeneous systems * Do not fuse ports if a mix of multi-port and single port are detected. Fix NVLS graphs search for dual NICs. * Fix NVLS graph search when we have more than one NIC per GPU. Fix crash with collnetDirect * Add separate graph search for collnetDirect, testing alltoall paths and working similarly to the NVLS search. Fix hang when nodes have different CPU types * Add the CPU type to the rank peer info. * Align all ranks on the CPU type after the first allgather. * Only use the aligned CPU type for all tuning operations. Fixes issue #1136 Fixes issue #1184 Fix performance of registered send/recv operations * Allow for single full size operations * Add INFO to confirm the registration of send/recv buffers. Move all sync ops to finalize stage * Ensure ncclCommDestroy is non-blocking if ncclCommFinalize has been called. Improve error reporting during SHM segment creation Improve support of various compilers Merges PR #1177 Merges PR #1228 Allow net and tuner plugins to be statically linked * Search for ncclNet or ncclTuner symbols in the main binary. Merges PR #979 Plugin examples includes cleanup * Harmonize err.h and common.h usage. * Add mixed plugin with both net and tuner.
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.