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CLARISSE: A Middleware for Data-Staging Coordination and Control on Large-Scale HPC Platforms
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-19129-4_14openalex-snapshot
Distributed Monitoring and Management of Exascale Systems in the Argo Project
inferredcites →https://doi.org/10.1016/j.advengsoft.2016.07.003openalex-snapshot
Making the case for reforming the I/O software stack of extreme-scale systems
inferredcites →https://doi.org/10.1016/j.jcp.2003.11.004openalex-snapshot
VORPAL: a versatile plasma simulation code
inferredcites →https://doi.org/10.1063/1.2840133openalex-snapshot
Ultrahigh performance three-dimensional electromagnetic relativistic kinetic plasma simulation
inferredcites →https://doi.org/10.1109/ccgrid.2008.85openalex-snapshot
View-Based Collective I/O for MPI-IO
inferredcites →https://doi.org/10.1109/ccgrid.2014.104openalex-snapshot
Flexpath: Type-Based Publish/Subscribe System for Large-Scale Science Analytics
inferredcites →https://doi.org/10.1109/ccgrid.2014.92openalex-snapshot
A Flexible Framework for Asynchronous in Situ and in Transit Analytics for Scientific Simulations
inferredcites →https://doi.org/10.1109/cluster.2012.26openalex-snapshot
Damaris: How to Efficiently Leverage Multicore Parallelism to Achieve Scalable, Jitter-free I/O
inferredcites →https://doi.org/10.1109/cluster.2014.6968744openalex-snapshot
POSTER: Leveraging deep memory hierarchies for data staging in coupled data-intensive simulation workflows
inferredcites →https://doi.org/10.1109/fmpc.1999.750599openalex-snapshot
Data sieving and collective I/O in ROMIO
inferredcites →https://doi.org/10.1109/icpp.2009.20openalex-snapshot
CIFTS: A Coordinated Infrastructure for Fault-Tolerant Systems
inferredcites →https://doi.org/10.1109/ipdps.2013.46openalex-snapshot
FlexIO: I/O Middleware for Location-Flexible Scientific Data Analytics
inferredcites →https://doi.org/10.1109/ipdps.2014.27openalex-snapshot
CALCioM: Mitigating I/O Interference in HPC Systems through Cross-Application Coordination
inferredcites →https://doi.org/10.1109/ipdps.2015.116openalex-snapshot
Scheduling the I/O of HPC Applications Under Congestion
inferredcites →https://doi.org/10.1109/ldav.2011.6092178openalex-snapshot
Toward simulation-time data analysis and I/O acceleration on leadership-class systems
inferredcites →https://doi.org/10.1109/sc.2008.5222721openalex-snapshot
Characterizing and predicting the I/O performance of HPC applications using a parameterized synthetic benchmark
inferredcites →https://doi.org/10.1109/sc.2014.18openalex-snapshot
The Lightweight Distributed Metric Service: A Scalable Infrastructure for Continuous Monitoring of Large Scale Computing Systems and Applications
inferredcites →https://doi.org/10.1145/1006209.1006219openalex-snapshot
Integrating collective I/O and cooperative caching into the "clusterfile" parallel file system
inferredcites →https://doi.org/10.1145/2063384.2063407openalex-snapshot
Server-side I/O coordination for parallel file systems
inferredcites →https://doi.org/10.1145/224170.224371openalex-snapshot
Server-directed collective I/O in Panda
inferredcites →https://doi.org/10.1145/2503210.2503278openalex-snapshot
Taming parallel I/O complexity with auto-tuning
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The many faces of publish/subscribe
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Storage Systems and Input/Output to Support Extreme Scale Science
inferredcites →https://doi.org/10.5555/1413370.1413413openalex-snapshot
Characterizing and predicting the I/O performance of HPC applications using a parameterized synthetic benchmark
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Cross‐layer coordination in the I/O software stack of extreme‐scale systems
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A Methodology for Handling Data Movements by Anticipation: Position Paper
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DICE: Generic Data Abstraction for Enhancing the Convergence of HPC and Big Data
inferred← citeshttps://doi.org/10.1007/978-3-031-40843-4_5openalex-snapshot
Malleable and Adaptive Ad-Hoc File System for Data Intensive Workloads in HPC Applications
inferred← citeshttps://doi.org/10.1007/s10951-021-00685-8openalex-snapshot
Scheduling periodic I/O access with bi-colored chains: models and algorithms
inferred← citeshttps://doi.org/10.1016/j.jss.2018.11.006openalex-snapshot
Combining malleability and I/O control mechanisms to enhance the execution of multiple applications
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LIMITLESS — LIght-weight MonItoring Tool for LargE Scale Systems
inferred← citeshttps://doi.org/10.1109/ccgrid.2017.55openalex-snapshot
Data-Aware Support for Hybrid HPC and Big Data Applications
inferred← citeshttps://doi.org/10.1109/ccgrid.2019.00046openalex-snapshot
Efficient Job Scheduling for Clusters with Shared Tiered Storage
inferred← citeshttps://doi.org/10.1109/ccgridw59191.2023.00071openalex-snapshot
Distributed and Dependable Software-Defined Storage Control Plane for HPC
inferred← citeshttps://doi.org/10.1109/cluster.2019.8891014openalex-snapshot
NORNS: Extending Slurm to Support Data-Driven Workflows through Asynchronous Data Staging
inferred← citeshttps://doi.org/10.1109/cluster48925.2021.00096openalex-snapshot
The Case for Storage Optimization Decoupling in Deep Learning Frameworks
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The 16,384-node Parallelism of 3D-CNN Training on An Arm CPU based Supercomputer
inferred← citeshttps://doi.org/10.1109/iccsnt56096.2022.9972985openalex-snapshot
A Connectivity Reduction Based Optimization Method for Task Level Parallel File System
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Sizing and Partitioning Strategies for Burst-Buffers to Reduce IO Contention
inferred← citeshttps://doi.org/10.1109/ipdps64566.2025.00072openalex-snapshot
A Deep Look into the Temporal I/O Behavior of HPC Applications
inferred← citeshttps://doi.org/10.1109/nas.2017.8026844openalex-snapshot
Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity
inferred← citeshttps://doi.org/10.1109/pdp52278.2021.00042openalex-snapshot
LIMITLESS - LIght-weight MonItoring Tool for LargE Scale Systems
inferred← citeshttps://doi.org/10.1109/scw63240.2024.00123openalex-snapshot
Can Current SDS Controllers Scale To Modern HPC Infrastructures?
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LoomIO: Object-Level Coordination in Distributed File Systems
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Understanding the Impact of Data Staging for Coupled Scientific Workflows
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I/O Scheduling Strategy for Periodic Applications
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A Survey and Classification of Software-Defined Storage Systems
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Mapping and scheduling HPC applications for optimizing I/O
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IO-aware Job-Scheduling: Exploiting the Impacts of Workload Characterizations to select the Mapping Strategy
inferred← citeshttps://doi.org/10.3390/electronics8090982openalex-snapshot
Performance-Aware Scheduling of Parallel Applications on Non-Dedicated Clusters
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Socket performance influence on data processing intensity in a virtual machine cluster with heterogeneous conditions.
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Tromos : a software development kit for virtual storage systems
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Resilient scheduling algorithms for large-scale platforms
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