From panda at cse.ohio-state.edu Sat Nov 5 09:14:43 2022 From: panda at cse.ohio-state.edu (Panda, Dhabaleswar) Date: Sat, 5 Nov 2022 13:14:43 +0000 Subject: [Hidl-discuss] Join the HiDL team for multiple events at SC '22 In-Reply-To: References: Message-ID: The HiDL team members will be participating in multiple events during Supercomputing '22 conference. The Ohio State University (OSU) booth (#4035) will also feature leading speakers from academia, national laboratories/centers, and industry!! Join us for these events and talk in person with the project team members and the invited speakers!! More details of the events are provided at: https://mvapich.cse.ohio-state.edu/conference/904/talks/ Alternatively, you can use the attached QR code to view the events. Pick-up a free T-shirt at the OSU Booth after attending the events! Please note that there will be a special session at The MIT Press Booth (#4301) on Nov. 14th 7:30-8:30 pm (during the Gala Opening session) to meet the authors of "High-Performance Big Data Computing" book and participate in a raffle to get free copies of this book (https://mitpress.mit.edu/9780262046855/high-performance-big-data-computing/) signed by the authors. The MIT Press is also offering a 20% discount for SC '22 attendees to purchase this book from their booth during the conference. Thanks, The HiDL Team -------------- next part -------------- A non-text attachment was scrubbed... Name: SC22-osu-booth-qr.png Type: image/png Size: 51114 bytes Desc: SC22-osu-booth-qr.png URL: From panda at cse.ohio-state.edu Sat Nov 12 09:15:32 2022 From: panda at cse.ohio-state.edu (Panda, Dhabaleswar) Date: Sat, 12 Nov 2022 14:15:32 +0000 Subject: [Hidl-discuss] Announcing the release of MPI4cuML 0.5 Message-ID: The High-Performance Deep Learning (HiDL) team is pleased to announce the release of MPI4cuML 0.5, which is a custom version of the cuML and associated RAFT libraries 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. This release of the cuML package is equipped with the following features: * MPI4cuML 0.5: - Based on cuML 22.02.00 - Include ready-to-use examples for KMeans, Linear Regression, Nearest Neighbors, and tSVD - MVAPICH2 support for RAFT 22.02.00 - Enabled cuML?s communication engine, RAFT, to use MVAPICH2-GDR backend for Python and C++ 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 (FDR and HDR) - Various x86-based multi-core platforms (AMD and Intel) - NVIDIA A100, 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 PS: The number of organizations using the HiDL stack has crossed 75 (from 39 countries). The HiDL team would like to thank all its users and organizations!!