AIACC-NCCL is an AI-Accelerator communication framework for NVIDIA-NCCL. It implements optimized all-reduce, all-gather, reduce, broadcast, reduce-scatter, all-to-all,as well as any send/receive based communication pattern.It has been optimized to achieve high bandwidth on aliyun machines using PCIe, NVLink, NVswitch,as well as networking using InfiniBand Verbs, eRDMA or TCP/IP sockets.
Project description
AIACC-NCCL
Optimized primitives for inter-GPU communication on Aliyun machines.
Introduction
AIACC-NCCL is an AI-Accelerator communication framework for NVIDIA-NCCL. It implements optimized all-reduce, all-gather, reduce, broadcast, reduce-scatter, all-to-all, as well as any send/receive based communication pattern. It has been optimized to achieve high bandwidth on aliyun machines using PCIe, NVLink, NVswitch, as well as networking using InfiniBand Verbs, eRDMA or TCP/IP sockets.
Install
To install AIACC NCCL on the system, create a package then install it as root as follow two methods:
- method1: rpm/deb (Recommended)
# Centos:
wget http://mirrors.aliyun.com/aiacc/aiacc-nccl/aiacc_nccl-1.0.rpm
rpm -i aiacc-nccl-1.0.rpm
# Ubuntu:
wget http://mirrors.aliyun.com/aiacc/aiacc-nccl/aiacc_nccl-1.0.deb
dpkg -i aiacc-nccl-1.0.deb
- method2: python-offline
wget http://mirrors.aliyun.com/aiacc/aiacc-nccl/aiacc_nccl-2.0.0.tar.gz
pip install aiacc_nccl-2.0.0.tar.gz
# notes: must download and then pip install, cannot merge in oneline `pip install aiacc_xxx_url`
# Both method1 and method2 can run concurrently.
- method3: python-pypi
pip install aiacc_nccl==2.0
Usage
After install aiacc-nccl package, you need do nothing to change code!
Environment
- AIACC_FASTTUNING: Enable Fasttuning for LLMs, default=1 is to enable.
- NCCL_AIACC_ALLREDUCE_DISABLE: Disable allreduce algo, default=0 is to enable.
- NCCL_AIACC_ALLGATHER_DISABLE: Disable allgather algo, default=0 is to enable.
- NCCL_AIACC_REDUCE_SCATTER_DISABLE: Disable reduce_scatter algo, default=0 is to enable.
- AIACC_UPDATE_ALGO_DISABLE: Disable update aiacc nccl algo from aiacc-sql-server, default=0 is to enable.
Performance
AIACC-NCCL can speedup the nccl performance on aliyun EGS(GPU machine), for example instance type 'ecs.ebmgn7ex.32xlarge' is A100 x 8 GPU and using network eRdma.
GPU(EGS) | Collective | Nodes | Network | Speedup(nccl-tests) |
---|---|---|---|---|
A100 x 8 | all_gather | 2-10 | VPC/eRdma | 30%+ |
A100 x 8 | reduce_scatter | 2-10 | VPC/eRdma | 30%+ |
A100 x 8 | all_reduce | 2-10 | VPC/eRdma | 20% |
V100 x 8 | all_reduce | 2-20 | VPC | 60%+ |
A10 x 8 | all_reduce | 1 | - | 20% |
Copyright
All source code and accompanying documentation is copyright (c) 2015-2020, NVIDIA CORPORATION. All rights reserved. All modifications are copyright (c) 2020-2024, ALIYUN CORPORATION. All rights reserved.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file aiacc-nccl-2.0.0.tar.gz
.
File metadata
- Download URL: aiacc-nccl-2.0.0.tar.gz
- Upload date:
- Size: 90.8 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 68d3d70234c9dd5d609c1e67a7453175d21c0efd95eb09b2519e98e86207c357 |
|
MD5 | ade007e7bc9d2d86bf9a2df3327cfeaa |
|
BLAKE2b-256 | 12a4b51dbb881c586c233c2ce5e12727fc6eba063ef503717209696181fd7b93 |