[Hidl-discuss] Announcing the release of MPI4cuML 0.1

[Panda, Dhabaleswar]

The High-Performance Deep Learning (HiDL) team is pleased to announce
the first release of MPI4cuML 0.1, which is a custom version of the
cuML library with support for the MVAPICH2 high-performance CUDA-aware
communication backend. The communication handle in cuML uses mpi4py
over the MVAPICH2-GDR library and targets modern HPC clusters built
with GPUs and high-performance interconnects.

The first release of the cuML package is equipped with the following
features:

* MPI4cuML 0.1:

    - Based on cuML 0.15
    - MVAPICH2 support for C++ and Python APIs
      - Included use of cuML C++ CUDA-Aware MPI example for KMeans clustering
      - Enabled cuML handles to use MVAPICH2-GDR backend for Python
        cuML applications
         - KMeans, PCA, tSVD, RF, LinearModels
         - Added switch between available communication backends
           (MVAPICH2 and NCCL)
    - Built on top of mpi4py over the MVAPICH2-GDR library
    - Tested with
      - Mellanox InfiniBand adapters
      - Various x86-based multi-core platforms (AMD and Intel)
      - NVIDIA V100 and P100 GPUs

For downloading the MPI4cuML package and the associated user guide,
please visit the following URL:

http://hidl.cse.ohio-state.edu

Sample performance numbers for MPI4cuML using machine learning
application benchmarks can be viewed by visiting the `Performance' tab
of the above website.

All questions, feedback, and bug reports are welcome. Please post to
hidl-discuss at lists.osu.edu.

Thanks,

The High-Performance Deep Learning (HiDL) Team
http://hidl.cse.ohio-state.edu