Skip to content

Add a coverage badge and some more README info #59

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
kshyatt merged 1 commit into from
Aug 19, 2025
Merged

Add a coverage badge and some more README info #59

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 8 additions & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,11 @@
NCCL.jl
=======

A Julia wrapper for the [NVIDIA Collective Communications Library (NCCL)](https://developer.nvidia.com/nccl).
[![codecov](https://codecov.io/gh/JuliaGPU/NCCL.jl/graph/badge.svg?token=1qbhp59GH1)](https://codecov.io/gh/JuliaGPU/NCCL.jl)

A Julia wrapper for the [NVIDIA Collective Communications Library (NCCL)](https://developer.nvidia.com/nccl). NCCL is an NVIDIA library
for multi-GPU *and* multi-node communication, optimized for NVIDIA GPUs. The API is designed to be similar to that of MPI, but there are
some differences. For example, unlike CUDA-aware MPI, NCCL can drive *multiple* devices per process. You can read more about how NCCL
compares with MPI [here](https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/mpi.html), and in fact the two can be used together.

NCCL is used internally in several other CUDA libraries, for example [cusolverMp](https://docs.nvidia.com/cuda/cusolvermp/index.html).
Loading