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Can RDMA benefit online data processing workloads on memcached and MySQL?

, , , , , and . ISPASS, page 159-160. IEEE Computer Society, (2015)

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Characterizing and benchmarking stand-alone Hadoop MapReduce on modern HPC clusters., , , , and . J. Supercomput., 72 (12): 4573-4600 (2016)SOR-HDFS: a SEDA-based approach to maximize overlapping in RDMA-enhanced HDFS., , , and . HPDC, page 261-264. ACM, (2014)SSD-Assisted Hybrid Memory to Accelerate Memcached over High Performance Networks., , , , , , and . ICPP, page 470-479. IEEE Computer Society, (2012)Understanding the communication characteristics in HBase: What are the fundamental bottlenecks?, , , , , , , , and . ISPASS, page 122-123. IEEE Computer Society, (2012)Does RDMA-based enhanced Hadoop MapReduce need a new performance model?, , , and . SoCC, page 45:1-45:2. ACM, (2013)High-Performance Hybrid Key-Value Store on Modern Clusters with RDMA Interconnects and SSDs: Non-blocking Extensions, Designs, and Benefits., , , , and . IPDPS, page 393-402. IEEE Computer Society, (2016)Accelerating Spark with RDMA for Big Data Processing: Early Experiences., , , , and . Hot Interconnects, page 9-16. IEEE Computer Society, (2014)A Micro-benchmark Suite for Evaluating Hadoop MapReduce on High-Performance Networks., , , , and . BPOE@ASPLOS/VLDB, volume 8807 of Lecture Notes in Computer Science, page 19-33. Springer, (2014)Can RDMA benefit online data processing workloads on memcached and MySQL?, , , , , and . ISPASS, page 159-160. IEEE Computer Society, (2015)Benchmarking key-value stores on high-performance storage and interconnects for web-scale workloads., , , , and . IEEE BigData, page 539-544. IEEE Computer Society, (2015)