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High-Performance Design of YARN MapReduce on Modern HPC Clusters with Lustre and RDMA
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-09873-9_54openalex-snapshot
MapReduce over Lustre: Can RDMA-Based Approach Benefit?
inferredcites →https://doi.org/10.1007/978-3-540-72586-2_111openalex-snapshot
Middleware in Modern High Performance Computing System Architectures
inferredcites →https://doi.org/10.1109/grid.2011.31openalex-snapshot
Using the Gfarm File System as a POSIX Compatible Storage Platform for Hadoop MapReduce Applications
inferredcites →https://doi.org/10.1109/hoti.2014.15openalex-snapshot
Accelerating Spark with RDMA for Big Data Processing: Early Experiences
inferredcites →https://doi.org/10.1109/icpp.2013.78openalex-snapshot
High-Performance Design of Hadoop RPC with RDMA over InfiniBand
inferredcites →https://doi.org/10.1109/ipdps.2012.74openalex-snapshot
High-Performance Design of HBase with RDMA over InfiniBand
inferredcites →https://doi.org/10.1109/ipdpsw.2013.238openalex-snapshot
High-Performance RDMA-based Design of Hadoop MapReduce over InfiniBand
inferredcites →https://doi.org/10.1109/msst.2010.5496972openalex-snapshot
The Hadoop Distributed File System
inferredcites →https://doi.org/10.1109/sc.2012.65openalex-snapshot
High performance RDMA-based design of HDFS over InfiniBand
inferredcites →https://doi.org/10.1145/2063384.2063461openalex-snapshot
Hadoop acceleration through network levitated merge
inferredcites →https://doi.org/10.1145/2063384.2063474openalex-snapshot
On the duality of data-intensive file system design
inferredcites →https://doi.org/10.21276/ijre.2018.5.5.4openalex-snapshot
MapReduce: Simplified Data Processing on Large Cluster
inferredcites →https://doi.org/10.5555/2388996.2389044openalex-snapshot
High performance RDMA-based design of HDFS over InfiniBand
inferredcites →https://doi.org/10.5555/2591272.2591287openalex-snapshot
MixApart: decoupled analytics for shared storage systems
inferredcites →https://doi.org/10.7551/mitpress/1556.001.0001openalex-snapshot
Beowulf Cluster Computing with Linux
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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OpenFAM: A Library for Programming Disaggregated Memory
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Experiences of Converging Big Data Analytics Frameworks with High Performance Computing Systems
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Customized Filesystem with Dynamic Stripe Strategies on Lustre-Based Hadoop
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Performance Assessment of the Map Reduce Framework with HDFS for High Availability and Fault Tolerance
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A Survey of RoCEv2 Congestion Control
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Characterizing and benchmarking stand-alone Hadoop MapReduce on modern HPC clusters
inferred← citeshttps://doi.org/10.1007/s11227-020-03162-9openalex-snapshot
Designing a MapReduce performance model in distributed heterogeneous platforms based on benchmarking approach
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Design and Implementation of the Tianhe-2 Data Storage and Management System
inferred← citeshttps://doi.org/10.1007/s11390-020-9801-1openalex-snapshot
Ad Hoc File Systems for High-Performance Computing
inferred← citeshttps://doi.org/10.1016/j.ins.2019.06.048openalex-snapshot
RDMA-driven MongoDB: An approach of RDMA enhanced NoSQL paradigm for large-Scale data processing
inferred← citeshttps://doi.org/10.1016/j.jpdc.2017.11.004openalex-snapshot
MR-Advisor: A comprehensive tuning, profiling, and prediction tool for MapReduce execution frameworks on HPC clusters
inferred← citeshttps://doi.org/10.1109/access.2017.2725318openalex-snapshot
Storage-Tag-Aware Scheduler for Hadoop Cluster
inferred← citeshttps://doi.org/10.1109/access.2019.2949836openalex-snapshot
Toward High-Performance Computing and Big Data Analytics Convergence: The Case of Spark-DIY
inferred← citeshttps://doi.org/10.1109/bdcat.2018.00010openalex-snapshot
Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models
inferred← citeshttps://doi.org/10.1109/bigdata.2015.7363761openalex-snapshot
Performance characterization and acceleration of in-memory file systems for Hadoop and Spark applications on HPC clusters
inferred← citeshttps://doi.org/10.1109/bigdata.2016.7840608openalex-snapshot
Efficient data access strategies for Hadoop and Spark on HPC cluster with heterogeneous storage
inferred← citeshttps://doi.org/10.1109/bigdata.2016.7840835openalex-snapshot
On-demand data analytics in HPC environments at leadership computing facilities: Challenges and experiences
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8257944openalex-snapshot
Big data and HPC collocation: Using HPC idle resources for Big Data analytics
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8257947openalex-snapshot
NVMD: Non-volatile memory assisted design for accelerating MapReduce and DAG execution frameworks on HPC systems
inferred← citeshttps://doi.org/10.1109/ccgrid.2015.161openalex-snapshot
Triple-H: A Hybrid Approach to Accelerate HDFS on HPC Clusters with Heterogeneous Storage Architecture
inferred← citeshttps://doi.org/10.1109/comst.2021.3094993openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/dasc-picom-datacom-cyberscitec.2017.160openalex-snapshot
Availability Modeling and Assurance of Map-Reduce Computing
inferred← citeshttps://doi.org/10.1109/hoti.2017.24openalex-snapshot
Characterizing Deep Learning over Big Data (DLoBD) Stacks on RDMA-Capable Networks
inferred← citeshttps://doi.org/10.1109/hpcc/smartcity/dss.2019.00069openalex-snapshot
Pream: Enhancing HPC Storage System Performance with Pre-Allocated Metadata Management Mechanism
inferred← citeshttps://doi.org/10.1109/icpp.2015.79openalex-snapshot
Accelerating I/O Performance of Big Data Analytics on HPC Clusters through RDMA-Based Key-Value Store
inferred← citeshttps://doi.org/10.1109/ipdps.2017.31openalex-snapshot
Mimir: Memory-Efficient and Scalable MapReduce for Large Supercomputing Systems
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Can Non-volatile Memory Benefit MapReduce Applications on HPC Clusters?
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MR-Advisor: A Comprehensive Tuning Tool for Advising HPC Users to Accelerate MapReduce Applications on Supercomputers
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DLoBD: A Comprehensive Study of Deep Learning over Big Data Stacks on HPC Clusters
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A Comprehensive Study of MapReduce Over Lustre for Intermediate Data Placement and Shuffle Strategies on HPC Clusters
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RF-RPC: Remote Fetching RPC Paradigm for RDMA-Enabled Network
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PostMan: Rapidly Mitigating Bursty Traffic via On-Demand Offloading of Packet Processing
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BoR: Toward High-Performance Permissioned Blockchain in RDMA-Enabled Network
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Accelerating Big Data Processing on Modern Clusters
inferred← citeshttps://doi.org/10.1145/2926534.2926538openalex-snapshot
On exploring efficient shuffle design for in-memory MapReduce
inferred← citeshttps://doi.org/10.1145/2949550.2949561openalex-snapshot
Experiences and Benefits of Running RDMA Hadoop and Spark on SDSC Comet
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Pinpointing crash-consistency bugs in the HPC I/O stack
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Big Data: desarrollo, avance y aplicación en las Organizaciones de la era de la Información
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RFP: A Remote Fetching Paradigm for RDMA-Accelerated Systems
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Lightweight distributed computing framework for orchestrating high performance computing and big data
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