[Hadoop-RDMA] Announcing the release of Hadoop-RDMA 0.9.8 package

[Panda, Dhabaleswar]

The Hadoop-RDMA team is pleased to announce the release of Hadoop-RDMA 0.9.8
package with the following features and bug-fixes:

* Hadoop-RDMA 0.9.8 Features

   - Based on Apache Hadoop 1.2.1
   - High performance design with native InfiniBand and RoCE support
     at the verbs-level for HDFS, MapReduce, and RPC components
   - Compliant with Apache Hadoop 1.2.1 APIs and applications
   - Easily configurable for native InfiniBand, RoCE and the traditional
     sockets-based support (Ethernet and InfiniBand with IPoIB)
   - HDFS over native InfiniBand and RoCE
       - RDMA-based write
       - RDMA-based replication
       - Tuned packet size
   - MapReduce over native InfiniBand and RoCE
       - RDMA-based shuffle
       - Pre-fetching and caching of map outputs
       - In-memory merge
       - Overlapping of merge and reduce
   - RPC over native InfiniBand and RoCE
       - JVM-bypassed buffer management
       - On-demand InfiniBand connection setup
       - RDMA or send/recv based adaptive communication
   - Tested with
       - Mellanox InfiniBand adapters (DDR, QDR, and FDR)
       - RoCE
       - Various multi-core platforms
       - Different file systems with disks and SSDs

* Bug Fixes (since 0.9.1)

   - MapReduce over InfiniBand
     - Reducing the waiting time for the pre-fetch cache read
     - Enabling Reduce tasks to randomize the shuffle pattern

   - HDFS over InfiniBand
     - Fix an issue in processing multiple blocks concurrently in a
       single task

For downloading Hadoop-RDMA 0.9.8 package and the associated user guide,
please visit the following URL:

http://hadoop-rdma.cse.ohio-state.edu

Sample performance numbers for benchmarks using Hadoop-RDMA 0.9.8
version can be viewed by visiting the `Performance' tab of the above website.

All questions, feedbacks and bug reports are welcome. Please post it
to the hadoop-rdma-discuss mailing list (hadoop-rdma-discuss at cse.ohio-state.edu).

Thanks,

The Hadoop-RDMA Team


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