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50 lines
3.4 KiB
Markdown
50 lines
3.4 KiB
Markdown
3 years ago
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---
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title: "The Ohio State University Announces Enhanced Support of Power Systems for High-Performance Computing"
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date: "2018-02-22"
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categories:
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- "blogs"
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tags:
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- "openpower"
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- "nvidia"
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- "infiniband"
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- "nvlink"
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- "openpower-foundation"
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- "ohio-state-university"
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- "department-of-computer-science-and-engineering"
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- "high-performance-mpi-and-deep-learning"
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- "rsma-hadoop-library"
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- "mvapich2"
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---
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By [Dhabaleswar](http://web.cse.ohio-state.edu/~panda.2/) K (DK) Panda, Professor and University Distinguished Scholar of Computer Science and Engineering, The Ohio State University
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The [Department of Computer Science and Engineering](https://cse.osu.edu/) at The Ohio State University has made major contributions to the field of high-performance computing for many years. Recently, our [Network Based Computing Lab](http://nowlab.cse.ohio-state.edu/) introduced two enhancements to further support the growth of computing on Power Systems.
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## **High-Performance MPI and Deep Learning on OpenPOWER**
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Our MVAPICH team now provides optimized support for OpenPOWER platforms with NVIDIA GPUs and NVLink to extract high-performance and scalability for MPI and Deep Learning applications. The latest MVAPICH2-GDR 2.3a release supports efficient CUDA IPC by exploiting multiple CUDA streams for multi-GPU systems with and without NVLink.
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Highlights of this release include:
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- Excellent MPI-level point-to-point communication for Device-to-Device (D-D), Device-to-Host (D-H) and Host-to-Host (H-H) paths, in addition to the CUDA-aware MPI design in the MVAPICH2-GDR library
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- Unidirectional bandwidth up to 35,390 Mbytes/sec for intra-node D-D communication
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- Bidirectional bandwidth up to 23,400 Mbytes/sec for inter-node D-D communication
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- High-performance and scalable collective communication support for broadcast, reduce and all-reduce, the common collective operations in Deep Learning.
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These features provide novel ways to extract the highest performance and scalability on the emerging CORAL systems with OpenPOWER, NVIDIA GPUs and InfiniBand.
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More than 2,800 organizations in 85 countries already use the MVAPICH2 library, including Sunway TaihuLight, the #1 SuperComputer in the world. For more information on the MVAPICH2-GDR 2.3 library and its performance figures, please [visit our website](http://mvapich.cse.ohio-state.edu/).
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## **RDMA-Hadoop Library Empowering OpenPOWER**
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Our HiBD (High-Performance Big Data) team now provides optimized designs and support in the RDMA-Hadoop library for OpenPOWER platforms with the InfiniBand network. New designs and optimized techniques are included in the latest RDMA-Hadoop 2.x 1.3.0 library to exploit the OpenPOWER architecture.
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Highlights of this release include:
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- The proposed designs can achieve up to 2.26X performance improvement for Hadoop workloads, compared to the default designs running on OpenPOWER platforms.
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- These features provide novel ways to extract the highest performance and scalability for big data workloads on the emerging OpenPOWER platforms with InfiniBand interconnect, such as upcoming CORAL systems.
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For more information on the RDMA-Hadoop 2.x 1.3.0 library and its performance figures, please [visit our website](http://hibd.cse.ohio-state.edu/).
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We are excited for the opportunities provided by both these recent releases and look forward to future improvements to high-performance computing leveraging Power Systems.
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