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High-Performance Multi-Rail Erasure Coding Library over Modern Data Center Architectures: Early Experiences.

, , , and . SoCC, page 530-531. ACM, (2018)

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MR-Advisor: A Comprehensive Tuning Tool for Advising HPC Users to Accelerate MapReduce Applications on Supercomputers., , , , and . SBAC-PAD, page 198-205. IEEE Computer Society, (2016)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)A Plugin-Based Approach to Exploit RDMA Benefits for Apache and Enterprise HDFS., , , , , and . BPOE, volume 9495 of Lecture Notes in Computer Science, page 119-132. Springer, (2015)Accelerating Spark with RDMA for Big Data Processing: Early Experiences., , , , and . Hot Interconnects, page 9-16. IEEE Computer Society, (2014)SCOR-KV: SIMD-Aware Client-Centric and Optimistic RDMA-Based Key-Value Store for Emerging CPU Architectures., , and . HiPC, page 257-266. IEEE, (2019)Accelerating I/O Performance of Big Data Analytics on HPC Clusters through RDMA-Based Key-Value Store., , , , and . ICPP, page 280-289. 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)SimdHT-Bench: Characterizing SIMD-Aware Hash Table Designs on Emerging CPU Architectures., , and . IISWC, page 178-188. IEEE, (2019)High-Performance and Resilient Key-Value Store with Online Erasure Coding for Big Data Workloads., , and . ICDCS, page 527-537. IEEE Computer Society, (2017)Triple-H: A Hybrid Approach to Accelerate HDFS on HPC Clusters with Heterogeneous Storage Architecture., , , , and . CCGRID, page 101-110. IEEE Computer Society, (2015)