On the public citation graph
High-performance design of apache spark with RDMA and its benefits on various workloads
0 signed · 75 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
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_29openalex-snapshot
Can Inter-VM Shmem Benefit MPI Applications on SR-IOV Based Virtualized Infiniband Clusters?
inferredcites →https://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
inferredcites →https://doi.org/10.1109/ccgrid.2013.76openalex-snapshot
SR-IOV Support for Virtualization on InfiniBand Clusters: Early Experience
inferredcites →https://doi.org/10.1109/ccgrid.2015.161openalex-snapshot
Triple-H: A Hybrid Approach to Accelerate HDFS on HPC Clusters with Heterogeneous Storage Architecture
inferredcites →https://doi.org/10.1109/ccgrid.2016.85openalex-snapshot
Towards Memory-Optimized Data Shuffling Patterns for Big Data Analytics
inferredcites →https://doi.org/10.1109/hipc.2014.7116876openalex-snapshot
High performance MPI library over SR-IOV enabled infiniband clusters
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/hpca.2014.6835958openalex-snapshot
BigDataBench: A big data benchmark suite from internet services
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.2016.105openalex-snapshot
MEMTUNE: Dynamic Memory Management for In-Memory Data Analytic Platforms
inferredcites →https://doi.org/10.1109/ipdpsw.2013.238openalex-snapshot
High-Performance RDMA-based Design of Hadoop MapReduce over InfiniBand
inferredcites →https://doi.org/10.21276/ijre.2018.5.5.4openalex-snapshot
MapReduce: Simplified Data Processing on Large Cluster
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.4703openalex-snapshot
Building a scientific workflow framework to enable real‐time machine learning and visualization
inferred← citeshttps://doi.org/10.1002/cpe.5189openalex-snapshot
Twister2: Design of a big data toolkit
inferred← citeshttps://doi.org/10.1002/cpe.6502openalex-snapshot
Twister2 Cross‐platform resource scheduler for big data
inferred← citeshttps://doi.org/10.1002/spe.2793openalex-snapshot
Big data deployment in containerized infrastructures through the interconnection of network namespaces
inferred← citeshttps://doi.org/10.1007/978-3-031-40843-4_29openalex-snapshot
An Earlier Experiences Towards Optimizing Apache Spark Over Frontera Supercomputer
inferred← citeshttps://doi.org/10.1007/978-3-319-63962-8_143-1openalex-snapshot
Performance Evaluation of Big Data Analysis
inferred← citeshttps://doi.org/10.1007/978-3-319-63962-8_143-2openalex-snapshot
Performance Evaluation of Big Data Analysis
inferred← citeshttps://doi.org/10.1007/978-3-319-77525-8_143openalex-snapshot
Performance Evaluation of Big Data Analysis
inferred← citeshttps://doi.org/10.1007/978-981-15-0146-3_67openalex-snapshot
Apache Spark Methods and Techniques in Big Data—A Review
inferred← citeshttps://doi.org/10.1007/978-981-16-7985-8_40openalex-snapshot
Implementation and Comparison of Big Data Analysis on Large Dataset Using SPARK and FLINK
inferred← citeshttps://doi.org/10.1007/978-981-99-8104-5_17openalex-snapshot
Congestion Control with Receiver-Aided Network Status Awareness in RDMA Transmission
inferred← citeshttps://doi.org/10.1007/s11390-023-2894-6openalex-snapshot
xCCL: A Survey of Industry-Led Collective Communication Libraries for Deep Learning
inferred← citeshttps://doi.org/10.1016/j.future.2018.04.030openalex-snapshot
BDEv 3.0: Energy efficiency and microarchitectural characterization of Big Data processing frameworks
inferred← citeshttps://doi.org/10.1016/j.future.2018.10.001openalex-snapshot
RHKV: An RDMA and HTM friendly key–value store for data-intensive computing
inferred← citeshttps://doi.org/10.1109/access.2018.2880842openalex-snapshot
Optimization of Real-World MapReduce Applications With Flame-MR: Practical Use Cases
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8257929openalex-snapshot
Performance characterization and acceleration of big data workloads on OpenPOWER system
inferred← citeshttps://doi.org/10.1109/bigdata.2018.8622088openalex-snapshot
Skew-Aware Collective Communication for MapReduce Shuffling
inferred← citeshttps://doi.org/10.1109/bigdata.2018.8622615openalex-snapshot
Spark-uDAPL: Cost-Saving Big Data Analytics on Microsoft Azure Cloud with RDMA Networks
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386120openalex-snapshot
MPI4Spark Meets YARN: Enhancing MPI4Spark through YARN support for HPC
inferred← citeshttps://doi.org/10.1109/cahpc.2018.8645858openalex-snapshot
Exploring the Potential of Next Generation Software-Defined in Memory Frameworks
inferred← citeshttps://doi.org/10.1109/ccgrid.2017.103openalex-snapshot
Swift-X: Accelerating OpenStack Swift with RDMA for Building an Efficient HPC Cloud
inferred← citeshttps://doi.org/10.1109/ccgrid.2019.00012openalex-snapshot
Optimizing Performance and Computing Resource Management of In-memory Big Data Analytics with Disaggregated Persistent Memory
inferred← citeshttps://doi.org/10.1109/ccgrid51090.2021.00037openalex-snapshot
Efficient MPI-based Communication for GPU-Accelerated Dask Applications
inferred← citeshttps://doi.org/10.1109/cic50333.2020.00019openalex-snapshot
Memory Abstraction and Optimization for Distributed Executors
inferred← citeshttps://doi.org/10.1109/cloud.2018.00055openalex-snapshot
Twister:Net - Communication Library for Big Data Processing in HPC and Cloud Environments
inferred← citeshttps://doi.org/10.1109/cluster.2018.00040openalex-snapshot
Cutting the Tail: Designing High Performance Message Brokers to Reduce Tail Latencies in Stream Processing
inferred← citeshttps://doi.org/10.1109/cluster59342.2025.11186496openalex-snapshot
Multi-agent Independent PPO-based Automatic ECN Tuning for High-Speed Data Center Networks
inferred← citeshttps://doi.org/10.1109/hipc.2018.00010openalex-snapshot
Accelerating TensorFlow with Adaptive RDMA-Based gRPC
inferred← citeshttps://doi.org/10.1109/hipc50609.2020.00025openalex-snapshot
Blink: Towards Efficient RDMA-based Communication Coroutines for Parallel Python Applications
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/hoti59126.2023.00022openalex-snapshot
Performance Characterization of Large Language Models on High-Speed Interconnects
inferred← citeshttps://doi.org/10.1109/icdcs47774.2020.00045openalex-snapshot
A Comprehensive Study of In-Memory Computing on Large HPC Systems
inferred← citeshttps://doi.org/10.1109/icpads53394.2021.00087openalex-snapshot
Infinileap: Modern High-Performance Networking for Distributed Java Applications based on RDMA
inferred← citeshttps://doi.org/10.1109/infocom42981.2021.9488875openalex-snapshot
Maximizing the Benefit of RDMA at End Hosts
inferred← citeshttps://doi.org/10.1109/ipdps49936.2021.00092openalex-snapshot
Argus: Efficient Job Scheduling in RDMA-assisted Big Data Processing
inferred← citeshttps://doi.org/10.1109/ipdpsw50202.2020.00123openalex-snapshot
Comparison of MPI and Spark for Data Science Applications
inferred← citeshttps://doi.org/10.1109/isncc.2019.8909103openalex-snapshot
Review of RDMA-enabled Consensus Protocols
inferred← citeshttps://doi.org/10.1109/ispdc.2019.00011openalex-snapshot
The Coming Age of Pervasive Data Processing
inferred← citeshttps://doi.org/10.1109/jiot.2025.3617973openalex-snapshot
An RDMA Congestion Control Enhancement Framework for Edge Datacenters
inferred← citeshttps://doi.org/10.1109/sbac-pad.2018.00042openalex-snapshot
Exploring the Potential of Next Generation Software-Defined in Memory Frameworks
inferred← citeshttps://doi.org/10.1109/tmscs.2018.2845886openalex-snapshot
DLoBD: A Comprehensive Study of Deep Learning over Big Data Stacks on HPC Clusters
inferred← citeshttps://doi.org/10.1109/tpds.2021.3092266openalex-snapshot
PostMan: Rapidly Mitigating Bursty Traffic via On-Demand Offloading of Packet Processing
inferred← citeshttps://doi.org/10.1109/trustcom60117.2023.00339openalex-snapshot
Transparent network acceleration for big data computing in Java
inferred← citeshttps://doi.org/10.1145/3225058.3225128openalex-snapshot
Task-parallel Analysis of Molecular Dynamics Trajectories
inferred← citeshttps://doi.org/10.1145/3297663.3310300openalex-snapshot
Analyzing and Optimizing Java Code Generation for Apache Spark Query Plan
inferred← citeshttps://doi.org/10.1145/3448016.3452816openalex-snapshot
DFI: The Data Flow Interface for High-Speed Networks
inferred← citeshttps://doi.org/10.1145/3600061.3600082openalex-snapshot
sRDMA: A General and Low-Overhead Scheduler for RDMA
inferred← citeshttps://doi.org/10.1145/3806645.3807582openalex-snapshot
When RDMA Goes Long-Haul: Characterization, Modeling, and Verbs-Level Emulation with Implications for Federated Learning
inferred← citeshttps://doi.org/10.1587/transinf.2019pap0019openalex-snapshot
Skew-Aware Collective Communication for MapReduce Shuffling
inferred← citeshttps://doi.org/10.1631/fitee.1800631openalex-snapshot
Networking and communication challenges for post-exascale systems
inferred← citeshttps://doi.org/10.22369/issn.2153-4136/11/1/1openalex-snapshot
Lessons Learned from the NASA-UVA Summer School and Internship Program
inferred← citeshttps://doi.org/10.3390/a18020074openalex-snapshot
Optimizing Apache Spark MLlib: Predictive Performance of Large-Scale Models for Big Data Analytics
inferred← citeshttps://doi.org/10.4018/978-1-6684-7105-0.ch012openalex-snapshot
Big Data Analytics-Based Agro Advisory System for Crop Recommendation Using Spark Platform
inferred← citeshttps://doi.org/10.70675/78ae30b9z5dedz4023z9547z8592909ee117openalex-snapshot
Intelligent Orchestration of High Performance, Scalable, and Correct Data Centres As a Network Service
inferred← citeshttps://doi.org/10.7551/mitpress/11451.001.0001openalex-snapshot
High-Performance Big Data Computing
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.