Observed since 21 Oct, 09:49 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
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.
Optimized primitives for inter-GPU communication on Aliyun machines.
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.
To install AIACC NCCL on the system, create a package then install it as root as follow two methods:
# 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
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.
pip install aiacc_nccl==2.0
After install aiacc-nccl package, you need do nothing to change code!
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% |
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.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 2.0.0 | 9 Oct 2023 | 0 |
This describes our collected data; it is not a security assessment.
Observed since 21 Oct, 09:49 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:689a1cf4f22e06aef4a16c775841cc710f3bfb4415ab6212b2804b7a370aa078